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WTFFF, a FREE open source agent harness that rewrites itself as it works nodecode runs as one live lisp image. add a tool, skill, mcp server or memory by dropping in a folder. works in your terminal, browser, discord, telegram and slack. FREE. you only pay for the model... show more

painn

10,188 subscribers

23,657 次观看 • 6 天前 •via X (Twitter)

科学技术教育

Anya Rossi• Live Now

Private livecam show

20 条评论

painn 的头像

painn6 天前

repo link

Miles S. 的头像

Miles S.6 天前

lisp was waiting for agents

MAX 的头像

MAX6 天前

Paying only for the model you use is a big plus. Lemme try it out

painn 的头像

painn6 天前

you can plug in free models

K2S 的头像

K2S6 天前

what model works best with it so far

painn 的头像

painn6 天前

try free models 🌚

Steven Cheng 的头像

Steven Cheng6 天前

rewrites itself" is the trap

painn 的头像

painn6 天前

ahah, give it a try first..

Ziwen 的头像

Ziwen6 天前

write itself at work?? Crazy

Draxx 的头像

Draxx6 天前

A live image that edits itself is the dream and the risk in one. The first bad tool it writes gets baked into the running image. Curious whether it snapshots before each self-edit so you can roll back, or if you just restart from the folders.

basedcapital 的头像

basedcapital6 天前

lowkey the live image never resets. state accumulating across sessions is great until the agent poisons its own memory with a bad rewrite at 3am and you cant figure out which version of itself youre debugging

Harshit Sehgal 的头像

Harshit Sehgal6 天前

a live image that rewrites itself is how lisp people always worked, fun watching agents rediscover it

Noaa 的头像

Noaa6 天前

giving the model just one tool, eval, is a bold call. committing every definition to git is what makes it easy to review

Luis Arca 的头像

Luis Arca5 天前

Sounds very powerful. Have you tried Hermes? How is it diferent ?

Alizeh 的头像

Alizeh5 天前

lisp good for this cuz code is data right

Bunyod 的头像

Bunyod5 天前

an agent that rewrites itself needs a way back. can you roll the image to a state from an hour ago if it breaks its own tool?

SunsetSyntax 的头像

SunsetSyntax6 天前

On first launch, setup imports keys, memory, skills and MCP servers from Claude Code, Codex and other agents on the machine without asking, and on Linux/macOS the gateway starts at login. eval has no sandbox, so README says use a container or VM. nodecode gateway off stops it.

Shubham Negi 的头像

Shubham Negi5 天前

Who can we use it in offensive security and bug bounty task ?

Yogi Yaramchitti 的头像

Yogi Yaramchitti6 天前

With a live lisp image the agent can hot-patch its own tools mid-run. What happens when a dropped-in skill breaks the image: is there a snapshot to roll back to, or does the agent have to debug itself while broken?

orvian 的头像

orvian6 天前

can’t miss this

相关视频

Today we're launching Jitsu MCP. This is an MCP server that lets your agent run your entire event pipeline directly in Claude Code, Claude Desktop, Cursor, or VS Code. Here's how it works: Add the server: claude mcp add --transport http jitsu Run this prompt: "Route my web stream into ClickHouse, but only purchase and signup events. Send a test event, check Live Events, and if anything errors, find the function in the path and fix it." Approve the OAuth prompt once, and all 26 tools are live Your agent wires the streams, watches Live Events, and rewrites a function when one of them throws. It runs the fix against a real event before shipping it, so nothing is persisted until it works. Every change lands in the audit log tagged mcp, so you can tell what the agent did from what a person did. It's all MIT licensed, and it runs against your own deployment. Jitsu is one of the fastest growing open-source CDPs with 5,000+ GitHub stars. Capturing events is unlimited and free, and delivery is free up to 200k events a month. Comment Jitsu and I'll DM you the exact prompts I run in Claude Code to build an event pipeline end to end.

Today we're launching Jitsu MCP. This is an MCP server that lets your agent run your entire event pipeline directly in Claude Code, Claude Desktop, Cursor, or VS Code. Here's how it works: Add the server: claude mcp add --transport http jitsu Run this prompt: "Route my web stream into ClickHouse, but only purchase and signup events. Send a test event, check Live Events, and if anything errors, find the function in the path and fix it." Approve the OAuth prompt once, and all 26 tools are live Your agent wires the streams, watches Live Events, and rewrites a function when one of them throws. It runs the fix against a real event before shipping it, so nothing is persisted until it works. Every change lands in the audit log tagged mcp, so you can tell what the agent did from what a person did. It's all MIT licensed, and it runs against your own deployment. Jitsu is one of the fastest growing open-source CDPs with 5,000+ GitHub stars. Capturing events is unlimited and free, and delivery is free up to 200k events a month. Comment Jitsu and I'll DM you the exact prompts I run in Claude Code to build an event pipeline end to end.

Soham Mehta

282,967 次观看 • 1 个月前

WTFFF, this is absolutely insane 😳 i replaced my $200/mo Claude plan for deepseek harness and it costs nothing deepseek dropped their agent harness 2 days ago. 99.7K stars already everything is a plugin. MIT. FREE and you can run it for $0; free models, no credit card here is how you set it up: 1. install node.js 2. run npx deepseek-ai/dsh web 3. open 4. settings → add custom provider → free model (any free model provider) done. full agent harness for $0 dev preview, expect breaking changes try it before they add upgrades

WTFFF, this is absolutely insane 😳 i replaced my $200/mo Claude plan for deepseek harness and it costs nothing deepseek dropped their agent harness 2 days ago. 99.7K stars already everything is a plugin. MIT. FREE and you can run it for $0; free models, no credit card here is how you set it up: 1. install node.js 2. run npx deepseek-ai/dsh web 3. open 4. settings → add custom provider → free model (any free model provider) done. full agent harness for $0 dev preview, expect breaking changes try it before they add upgrades

painn

203,976 次观看 • 2 个月前

HERMES AGENT WITHOUT TOOLS IS A CHATBOT. WITH THEM IT BUILDS 3D TOWERS IN BLENDER, CHECKS STOCK PRICES, AND DRIVES VS CODE. tonbi JUST DROPPED THE FULL GUIDE. module 6 of his 10-part Hermes masterclass. best breakdown of the tool layer anyone has published. what you need to know: TOOLS vs SKILLS vs MCP skills = instructions (markdown, loaded into context) tools = callable functions (Python, agent emits call, Hermes executes) MCP = adapters to external systems (Blender, Stripe, Linear, Notion) every tool has three parts: → the function (does the real work) → the schema (what the model sees to decide when to call it) → the registry (makes the tool exist in the agent) the model never runs the function directly. it emits a structured request (tool name + JSON args). Hermes executes and returns the result. if the tool fails, the error goes back as JSON. the agent recovers instead of crashing. TOOL SETS CONTROL THE SURFACE hermes chat --tool-sets web # only web tools loaded. no files, no terminal. hermes chat --tool-sets safe # read-only: web search, vision, image gen. # no file writes. no terminal. no code execution. mid-session: /tools enable video /tools disable terminal or toggle in the dashboard: hermes dashboard → Skills → Tool Sets MCP SERVERS two transport types: STDIO (local subprocess) or HTTP (remote endpoint). add a server: hermes mcp # or ask: "add the MCP server for Blender" filter tools with include/exclude per server. keep only what you trust. security: → OAuth 2.1 PKCE (no long-lived tokens in config) → package scanning via api.osv. dev before launch → all MCP calls go through approval gates HERMES AS MCP SERVER hermes mcp serve exposes 10 tools via FastMCP. connect VS Code Copilot or Cursor to your running Hermes instance. BUILD YOUR OWN TOOL He built a stock price tool live: → Python function calling Finnhub API → schema with name, description, parameters → registered in tool_sets.py → agent calls it automatically when relevant any repeating API call in your workflow can become a native tool. full Hermes architecture deep-dive in the article 👇

HERMES AGENT WITHOUT TOOLS IS A CHATBOT. WITH THEM IT BUILDS 3D TOWERS IN BLENDER, CHECKS STOCK PRICES, AND DRIVES VS CODE. tonbi JUST DROPPED THE FULL GUIDE. module 6 of his 10-part Hermes masterclass. best breakdown of the tool layer anyone has published. what you need to know: TOOLS vs SKILLS vs MCP skills = instructions (markdown, loaded into context) tools = callable functions (Python, agent emits call, Hermes executes) MCP = adapters to external systems (Blender, Stripe, Linear, Notion) every tool has three parts: → the function (does the real work) → the schema (what the model sees to decide when to call it) → the registry (makes the tool exist in the agent) the model never runs the function directly. it emits a structured request (tool name + JSON args). Hermes executes and returns the result. if the tool fails, the error goes back as JSON. the agent recovers instead of crashing. TOOL SETS CONTROL THE SURFACE hermes chat --tool-sets web # only web tools loaded. no files, no terminal. hermes chat --tool-sets safe # read-only: web search, vision, image gen. # no file writes. no terminal. no code execution. mid-session: /tools enable video /tools disable terminal or toggle in the dashboard: hermes dashboard → Skills → Tool Sets MCP SERVERS two transport types: STDIO (local subprocess) or HTTP (remote endpoint). add a server: hermes mcp # or ask: "add the MCP server for Blender" filter tools with include/exclude per server. keep only what you trust. security: → OAuth 2.1 PKCE (no long-lived tokens in config) → package scanning via api.osv. dev before launch → all MCP calls go through approval gates HERMES AS MCP SERVER hermes mcp serve exposes 10 tools via FastMCP. connect VS Code Copilot or Cursor to your running Hermes instance. BUILD YOUR OWN TOOL He built a stock price tool live: → Python function calling Finnhub API → schema with name, description, parameters → registered in tool_sets.py → agent calls it automatically when relevant any repeating API call in your workflow can become a native tool. full Hermes architecture deep-dive in the article 👇

YanXbt

32,680 次观看 • 4 个月前

I truly don't understand why nobody is using this setup graphify, a tool that turns any folder into a knowledge graph your agent can query, just passed 126k stars on github and got into Y Combinator. people stopped asking ai questions. they're giving it a desk, a memory and a job. you give Claude Code one folder, plug in your email, calendar and a browser, and it turns into an agent. it reads, remembers, acts, and checks itself before it does anything stupid. doesn't matter if you're a founder, a marketer or a student, you need this the full setup: > create a folder called AGENT, open Claude Code inside it and add a CLAUDE.md with one rule: "save every decision, person and project to memory/" > run npm install -g @googleworkspace/cli, then gws auth setup. now it reads your Gmail, Calendar and Drive > run claude mcp add playwright npx @playwright/mcp@latest. it gets its own browser to open sites, fill forms and pull data for you > run uv tool install graphifyy, then graphify install, then type /graphify .. everything in the folder becomes a knowledge graph it queries in seconds instead of digging file by file > run npm i -g jev-guard, jev-guard key "...", jev-guard install claude. a tiny model called Jev scores every action before it runs. rm -rf gets blocked, a poisoned email gets flagged, for about 4 cents per 1,000 checks > type /schedule and tell it "every morning at 7:30, send me what came in, what you drafted and what waits for my yes". from now on it works on a routine 15 minutes to set up, and you never start from a blank chat again. every repo is below: -> -> -> -> bookmark this

I truly don't understand why nobody is using this setup graphify, a tool that turns any folder into a knowledge graph your agent can query, just passed 126k stars on github and got into Y Combinator. people stopped asking ai questions. they're giving it a desk, a memory and a job. you give Claude Code one folder, plug in your email, calendar and a browser, and it turns into an agent. it reads, remembers, acts, and checks itself before it does anything stupid. doesn't matter if you're a founder, a marketer or a student, you need this the full setup: > create a folder called AGENT, open Claude Code inside it and add a CLAUDE.md with one rule: "save every decision, person and project to memory/" > run npm install -g @googleworkspace/cli, then gws auth setup. now it reads your Gmail, Calendar and Drive > run claude mcp add playwright npx @playwright/mcp@latest. it gets its own browser to open sites, fill forms and pull data for you > run uv tool install graphifyy, then graphify install, then type /graphify .. everything in the folder becomes a knowledge graph it queries in seconds instead of digging file by file > run npm i -g jev-guard, jev-guard key "...", jev-guard install claude. a tiny model called Jev scores every action before it runs. rm -rf gets blocked, a poisoned email gets flagged, for about 4 cents per 1,000 checks > type /schedule and tell it "every morning at 7:30, send me what came in, what you drafted and what waits for my yes". from now on it works on a routine 15 minutes to set up, and you never start from a blank chat again. every repo is below: -> -> -> -> bookmark this

kiosa

109,215 次观看 • 13 天前

I just built my second brain with Hermes Agent. It remembers people, companies, projects, and decisions. It pulls from meeting notes, docs, anything I feed it, and cites the source every time. It's this repo called Gbrain, open-sourced by Y Combinator president Garry Tan. install it by pasting this into Hermes: "Install Gbrain following the instructions at Set up the embedding provider, then run gbrain init and gbrain doctor to verify." Add the MCP server so Hermes can call it directly: "Add the Gbrain MCP server and reload." The graph builds itself. Pattern matching on the people and companies already in your notes. 31 points more precise than plain vector search, by their own benchmark. The data from the video is made up so I could show you how it works. Hermes' memory remembers our conversations. Gbrain remembers my world. Open source. Runs local, no server, no Docker.

I just built my second brain with Hermes Agent. It remembers people, companies, projects, and decisions. It pulls from meeting notes, docs, anything I feed it, and cites the source every time. It's this repo called Gbrain, open-sourced by Y Combinator president Garry Tan. install it by pasting this into Hermes: "Install Gbrain following the instructions at Set up the embedding provider, then run gbrain init and gbrain doctor to verify." Add the MCP server so Hermes can call it directly: "Add the Gbrain MCP server and reload." The graph builds itself. Pattern matching on the people and companies already in your notes. 31 points more precise than plain vector search, by their own benchmark. The data from the video is made up so I could show you how it works. Hermes' memory remembers our conversations. Gbrain remembers my world. Open source. Runs local, no server, no Docker.

Alvaro Cintas

16,975 次观看 • 3 个月前

grok-bot just got open-sourced and it run locally completely FREE. 3.8k stars in 2 weeks. MIT licensed. it gives every AI agent its own computer. own browser, own files, own container. every action is approved against a policy before it runs, and written to an audit log after. here's how to set it up: 1️⃣prerequisites Docker + Bun 1.3+ 2️⃣clone and create your env git clone cd OpenBot cp .env.example .env 3️⃣get intelligence credentials (free plan works) npx --yes copilotkit@latest login npx --yes copilotkit@latest project select npx --yes copilotkit@latest license --write drop the cpk-... key into .env as INTELLIGENCE_API_KEY 4️⃣ add your model key "OPENAI_API_KEY=sk-..." 5️⃣ run it bun install bash scripts/start.sh open localhost:3010. that's it. the underrated part: the repo ships a prompt.txt you paste into claude code or cursor and it walks the whole setup for you. every claim in it is verified against the actual repo. what it actually costs: the code is MIT, free forever. you pay your own model tokens. intelligence has a free tier and can be fully self-hosted if you want zero external dependency. works with any AG-UI agent. langgraph, mastra, crewai, pydantic ai. repo in in the CS.

grok-bot just got open-sourced and it run locally completely FREE. 3.8k stars in 2 weeks. MIT licensed. it gives every AI agent its own computer. own browser, own files, own container. every action is approved against a policy before it runs, and written to an audit log after. here's how to set it up: 1️⃣prerequisites Docker + Bun 1.3+ 2️⃣clone and create your env git clone cd OpenBot cp .env.example .env 3️⃣get intelligence credentials (free plan works) npx --yes copilotkit@latest login npx --yes copilotkit@latest project select npx --yes copilotkit@latest license --write drop the cpk-... key into .env as INTELLIGENCE_API_KEY 4️⃣ add your model key "OPENAI_API_KEY=sk-..." 5️⃣ run it bun install bash scripts/start.sh open localhost:3010. that's it. the underrated part: the repo ships a prompt.txt you paste into claude code or cursor and it walks the whole setup for you. every claim in it is verified against the actual repo. what it actually costs: the code is MIT, free forever. you pay your own model tokens. intelligence has a free tier and can be fully self-hosted if you want zero external dependency. works with any AG-UI agent. langgraph, mastra, crewai, pydantic ai. repo in in the CS.

m0h

59,144 次观看 • 1 个月前

We’re excited to launch OpenMemory MCP, a private memory for MCP-compatible clients powered by mem0 Today, most AI assistants and dev tools operate without memory. You plan your roadmap in Claude, implement tasks in Cursor, but none of them know what the other did. Each tool operates in isolation, and your context disappears as soon as the session ends. OpenMemory MCP solves this. Built on the open Model Context Protocol (MCP), OpenMemory MCP runs 100% locally and provides a persistent, portable memory layer for all your AI tools. It enables agents and assistants to read from and write to a shared memory, securely and privately. Key capabilities: ✅Works across MCP clients like Cursor, Claude Desktop, Windsurf, Cline and more ✅Provides standardized memory operations (add_memories, search_memory, list_memories, delete_all_memories) ✅Stores data on your machine, fully private ✅Offers a centralized dashboard for visibility and control ✅Simple Docker-based setup with no vendor lock-in If you're building on MCP, OpenMemory MCP is the easiest way to add persistent, private memory to your clients with zero cloud dependencies and full local control. We’ve put together a short demo to show how it works Check it out in the links below 👇

We’re excited to launch OpenMemory MCP, a private memory for MCP-compatible clients powered by mem0 Today, most AI assistants and dev tools operate without memory. You plan your roadmap in Claude, implement tasks in Cursor, but none of them know what the other did. Each tool operates in isolation, and your context disappears as soon as the session ends. OpenMemory MCP solves this. Built on the open Model Context Protocol (MCP), OpenMemory MCP runs 100% locally and provides a persistent, portable memory layer for all your AI tools. It enables agents and assistants to read from and write to a shared memory, securely and privately. Key capabilities: ✅Works across MCP clients like Cursor, Claude Desktop, Windsurf, Cline and more ✅Provides standardized memory operations (add_memories, search_memory, list_memories, delete_all_memories) ✅Stores data on your machine, fully private ✅Offers a centralized dashboard for visibility and control ✅Simple Docker-based setup with no vendor lock-in If you're building on MCP, OpenMemory MCP is the easiest way to add persistent, private memory to your clients with zero cloud dependencies and full local control. We’ve put together a short demo to show how it works Check it out in the links below 👇

Taranjeet

472,497 次观看 • 1 年前

It is becoming f*cking dangerous: the NSA's own reverse-engineering tool now plugs straight into Claude Code - Ghidra has 94k stars, and GhidraMCP lets your agent read a compiled program instead of guessing what it does Install Ghidra 12.1.4 from ghidra-sre,org (free, released by the NSA) Download the GhidraMCP release and add it in File -> Install Extensions Restart Ghidra and switch on GhidraMCPPlugin in File -> Configure -> Developer Connect it: claude mcp add ghidra -- uvx --from git+ ghidra-mcp Open a binary you're allowed to analyze and let Ghidra run its analysis Ask Claude what a function does: it decompiles it, renames the variables and explains it in plain English Ask for the map: every function, import, string and cross-reference, and where the interesting code lives The decompiling runs in Ghidra on your machine, Claude just drives it Malware samples, old firmware, your own builds: your agent reads the program itself, not the docs about it Find the repo in the reply below

It is becoming f*cking dangerous: the NSA's own reverse-engineering tool now plugs straight into Claude Code - Ghidra has 94k stars, and GhidraMCP lets your agent read a compiled program instead of guessing what it does Install Ghidra 12.1.4 from ghidra-sre,org (free, released by the NSA) Download the GhidraMCP release and add it in File -> Install Extensions Restart Ghidra and switch on GhidraMCPPlugin in File -> Configure -> Developer Connect it: claude mcp add ghidra -- uvx --from git+ ghidra-mcp Open a binary you're allowed to analyze and let Ghidra run its analysis Ask Claude what a function does: it decompiles it, renames the variables and explains it in plain English Ask for the map: every function, import, string and cross-reference, and where the interesting code lives The decompiling runs in Ghidra on your machine, Claude just drives it Malware samples, old firmware, your own builds: your agent reads the program itself, not the docs about it Find the repo in the reply below

Archive

16,420 次观看 • 5 天前

Ship a new eve agent in one minute. From 1. Add a prompt 2. Pick models & MCP connections 3. Deploy Your agent is in production, ready to chat, backed by a Git repo you own.

Ship a new eve agent in one minute. From 1. Add a prompt 2. Pick models & MCP connections 3. Deploy Your agent is in production, ready to chat, backed by a Git repo you own.

Vercel

142,982 次观看 • 2 个月前

THIS GUY VIBE CODED A TOOL THAT TURNS ANY SVG INTO A 3D OBJECT YOU CAN SPIN, ANIMATE, AND EMBED drag in an SVG, type some text, or draw pixel art. it becomes a 3D object instantly. spin it around, animate it, and embed it on your site. export as 4K image or video. runs entirely in your browser and nothing gets uploaded to any server with no account needed. 100% free AND its open source. this is one of those tools you didn't know you needed until you see it

THIS GUY VIBE CODED A TOOL THAT TURNS ANY SVG INTO A 3D OBJECT YOU CAN SPIN, ANIMATE, AND EMBED drag in an SVG, type some text, or draw pixel art. it becomes a 3D object instantly. spin it around, animate it, and embed it on your site. export as 4K image or video. runs entirely in your browser and nothing gets uploaded to any server with no account needed. 100% free AND its open source. this is one of those tools you didn't know you needed until you see it

Om Patel

231,576 次观看 • 6 个月前

Cline can now create and add tools to himself using MCP! Try asking him to “add a tool that pulls the latest npm docs” - Cline handles everything from creating the MCP server to installing it *into himself*, ready for future tasks. Servers are saved in ~/Documents/Cline/MCP so you can easily share tools with friends!

Cline can now create and add tools to himself using MCP! Try asking him to “add a tool that pulls the latest npm docs” - Cline handles everything from creating the MCP server to installing it into himself, ready for future tasks. Servers are saved in ~/Documents/Cline/MCP so you can easily share tools with friends!

Saoud Rizwan

62,208 次观看 • 1 年前

API-first email built for AI agents One prompt to plug in via MCP or Agent Skill Your agent gets its own inbox – and can run any workflow over email Free in open alpha - link in comments

API-first email built for AI agents One prompt to plug in via MCP or Agent Skill Your agent gets its own inbox – and can run any workflow over email Free in open alpha - link in comments

Atomic Mail

219,609 次观看 • 4 个月前

this tweet misses the gold of executor! the whole point is you don't want CLI / scripts, you want API / MCP servers in this video i ask executor to configure itself and add an MCP server - it pops up a browser for me to OAuth through based on the MCP elicitation spec

this tweet misses the gold of executor! the whole point is you don't want CLI / scripts, you want API / MCP servers in this video i ask executor to configure itself and add an MCP server - it pops up a browser for me to OAuth through based on the MCP elicitation spec

Rhys

33,637 次观看 • 7 个月前

Someone paid $6,000 (!) to get OpenClaw setup. So I built a free, open-source alternative: > OpenClaw Operator It's an agent skill + AGENTS.md/CLAUDE.md file that gives Codex/Claude Code the playbooks + validation flow needed to configure your local OpenClaw install. You open your OpenClaw repo/workspace in your coding agent and say things like: - “set up a cron job” - “create a custom skill” - “fix my provider config” - “troubleshoot this install and validate it” Nothing magical. Uses context from the OpenClaw open-source repo + docs to provide an effective skill. Includes: - SKILL.md - AGENTS.md/CLAUDE.md - validation checklist - task playbooks Free and open source. Contributions welcome. Demo below. Repo in reply.

Someone paid $6,000 (!) to get OpenClaw setup. So I built a free, open-source alternative: > OpenClaw Operator It's an agent skill + AGENTS.md/CLAUDE.md file that gives Codex/Claude Code the playbooks + validation flow needed to configure your local OpenClaw install. You open your OpenClaw repo/workspace in your coding agent and say things like: - “set up a cron job” - “create a custom skill” - “fix my provider config” - “troubleshoot this install and validate it” Nothing magical. Uses context from the OpenClaw open-source repo + docs to provide an effective skill. Includes: - SKILL.md - AGENTS.md/CLAUDE.md - validation checklist - task playbooks Free and open source. Contributions welcome. Demo below. Repo in reply.

Dan McAteer

17,859 次观看 • 7 个月前

someone built a free open-source version of manus. no invite code needed. it's called OpenManus. built in 3 hours by researchers from metagpt. give it any task via terminal and it handles everything end to end: ✦ plans and reasons through the task ✦ browses the web autonomously ✦ uses tools and executes actions ✦ mcp support included ✦ works with any llm provider 100% free. open source.

someone built a free open-source version of manus. no invite code needed. it's called OpenManus. built in 3 hours by researchers from metagpt. give it any task via terminal and it handles everything end to end: ✦ plans and reasons through the task ✦ browses the web autonomously ✦ uses tools and executes actions ✦ mcp support included ✦ works with any llm provider 100% free. open source.

Oliver Prompts

58,278 次观看 • 3 个月前

How to connect Agent Wallet to your AI agent. → MCP: add our MCP server to Claude, sign in with District Pass. → CLI: install the fdx CLI, sign up or log in via email OTP, run in Claude Code. Now your AI agent doesn't just talk. It pays, swaps, and earns. Get Started →

How to connect Agent Wallet to your AI agent. → MCP: add our MCP server to Claude, sign in with District Pass. → CLI: install the fdx CLI, sign up or log in via email OTP, run in Claude Code. Now your AI agent doesn't just talk. It pays, swaps, and earns. Get Started →

Finance District

18,293 次观看 • 4 个月前

Introducing Document Extraction as an MCP Server ✂️📑 A huge use case for AI agents is being able to extract out items from a diverse set of complex documents in a repeatable manner - whether it’s legal contracts, invoices, financial statements, passports, and more. In this case, 🚫 prompting ChatGPT/Claude is too error-prone/not systematic. 💡We’ve created a plug-and-play MCP server around our core document extraction capabilities within LlamaCloud. 1. Build an extraction agent in LlamaCloud with a standardized schema. 2. Plug it as an MCP tool within ChatGPT/Claude. 3. For your next extraction job, get the outputs in a standardized format through the tool! Huge shoutout to Tuana and Logan Markewich for working on this - this is thanks to the latest updates to our llamacloud-mcp demo repo, which supports both extraction and retrieval as MCP tools. Repo: Sign up:

Introducing Document Extraction as an MCP Server ✂️📑 A huge use case for AI agents is being able to extract out items from a diverse set of complex documents in a repeatable manner - whether it’s legal contracts, invoices, financial statements, passports, and more. In this case, 🚫 prompting ChatGPT/Claude is too error-prone/not systematic. 💡We’ve created a plug-and-play MCP server around our core document extraction capabilities within LlamaCloud. 1. Build an extraction agent in LlamaCloud with a standardized schema. 2. Plug it as an MCP tool within ChatGPT/Claude. 3. For your next extraction job, get the outputs in a standardized format through the tool! Huge shoutout to Tuana and Logan Markewich for working on this - this is thanks to the latest updates to our llamacloud-mcp demo repo, which supports both extraction and retrieval as MCP tools. Repo: Sign up:

Jerry Liu

57,827 次观看 • 1 年前

Not one, but six new Agent Skills! Early adopters improved Xcode build times by 78%. After weeks of work, I launched my latest Agent Skill at Let’s Vision in Shanghai. Here’s how it works: It runs 3 clean + 3 incremental builds It analyzes build logs and project settings It proposes an optimization plan It applies improvements after you approve It re-benchmarks and reports the improvement All free → try it on your Xcode projects. Let me know how it goes in the replies, and open a PR if you add your results to the README!

Not one, but six new Agent Skills! Early adopters improved Xcode build times by 78%. After weeks of work, I launched my latest Agent Skill at Let’s Vision in Shanghai. Here’s how it works: It runs 3 clean + 3 incremental builds It analyzes build logs and project settings It proposes an optimization plan It applies improvements after you approve It re-benchmarks and reports the improvement All free → try it on your Xcode projects. Let me know how it goes in the replies, and open a PR if you add your results to the README!

Antoine v.d. SwiftLee 

134,505 次观看 • 7 个月前

HERMES AGENT JUST SHIPPED A PROFILE BUILDER IN THE DASHBOARD. build a complete agent in one guided flow. no CLI. no config editing. no guesswork. Nous Research open Profiles from the sidebar. click Build (next to quick Create). follow the 5-step wizard: Identity → Model → Skills → MCPs → Review IDENTITY → name, description, SOUL.md → this becomes slot #1 in the system prompt MODEL → pick provider and model for this agent → same 150+ config fields available in the dashboard SKILLS → toggle built-in and optional skills → search the Skills Hub across all sources → install with live progress log → update all installed skills in one click MCPs → add HTTP/SSE servers by URL → add stdio servers by command + args + env vars → browse the Nous-approved MCP catalog → one-click install from catalog → test any server before committing (connect → list tools → verify → disconnect) REVIEW → full summary of the new agent → confirm and deploy one wizard replaces: hermes profile create, manual SOUL.md edit, config.yaml changes, skills install one by one, MCP setup via CLI. hermes dashboard → Profiles → Build 8 loops inside Hermes Agent 👇

YanXbt

13,563 次观看 • 4 个月前

HERMES AGENT JUST GOT A RESEARCH BRAIN. connect it to NotebookLM and it becomes a 247 research system that builds knowledge over time. it resources. connects ideas across sources. uses that context in every real task. setup in 4 steps: 1. install Hermes with MCP enabled 2. download NotebookLM skill from GitHub 3. add endpoint to MCP servers in config 4. restart Hermes what your agent can now do: → query your notebooks instead of the open web → connect ideas across multiple sources → build knowledge session after session → use your curated context in every /goal → zero hallucinations from your own verified sources ask it anything — it answers from what YOU already know. full setup guide — MCP, models, use cases — in the article 👇

HERMES AGENT JUST GOT A RESEARCH BRAIN. connect it to NotebookLM and it becomes a 247 research system that builds knowledge over time. it resources. connects ideas across sources. uses that context in every real task. setup in 4 steps: 1. install Hermes with MCP enabled 2. download NotebookLM skill from GitHub 3. add endpoint to MCP servers in config 4. restart Hermes what your agent can now do: → query your notebooks instead of the open web → connect ideas across multiple sources → build knowledge session after session → use your curated context in every /goal → zero hallucinations from your own verified sources ask it anything — it answers from what YOU already know. full setup guide — MCP, models, use cases — in the article 👇

YanXbt

187,943 次观看 • 5 个月前