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It's going live. My stock market API now has coverage for all S&P 500 tickers. • income statements • balance sheets • cash flow statements 30+ years of data. No API limits. You can connect your AI financial agents to this data. This open beta will run for ~1... show more

Virat Singh

50,247 subscribers

101,583 views • 2 years ago •via X (Twitter)

Finance Science & Technology

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11 Comments

virat2 years ago

api: docs: discord:

virat2 years ago

already have someone trying to anonymously scrape the API 😄

swyx /dd2 years ago

what was your motivation in starting this? also wondering if youve talked to OpenBB

virat2 years ago

I built a portfolo management platform once. ad a solo developer, getting high quality financial data was extremely painful

geordi2 years ago

Love the trust, hope no one abuses that by copying all the data 🙏 best of luck, cool project to watch built in public!

virat2 years ago

It’s fine if they do - the API is for developers! I’m adding usage-based billing this week which will support infra costs

Denzel Jacques2 years ago

Should I build a financial advisor based on it? What a coincidence! I wanted to look into this area recently. Great job!

virat2 years ago

You absolutely should. Lmk how I can help

Hassan2 years ago

Very cool! Might build a side project using your API 👀

Sandra Kublik2 years ago

congrats on shipping! 🥳

virat2 years ago

Thanks Sandra!

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It's happening. Last night, I started downloading financial data from the SEC. • income statements • balance sheets • cash flow statements 10,000+ public companies. 3 million rows in total. I’m using multiple worker nodes to pull, parse, and clean the data. The orchestration is beautiful. This week, I will: • create an API for accessing the data • write and publish developer docs • add auth so you can use it cc buildspace nights & weekends 🔊 on for the video

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Virat Singh

313,830 views • 2 years ago

I built a stock market API in 42 days. All during buildspace s5. What is the API? Today, it lets you pull financials for 16,000 tickers going back 30+ years. Why did I build the API? Because the big providers have: • poor API design • poor documentation • expensive sales contracts • strict data retention policies How did I build it? I started building the API from scratch at the start of s5 in early June. I got deep into the SEC Edgar API and cracked how to scrape at scale. Sonnet 3.5 from Anthropic was a godsend for this. I hacked early mornings, late nights, and weekends, with a full-time job. Day by day. Code by code. I set weekly goals and hit each one. End result: I’m excited to see where this API goes. It may go nowhere, but I’ll always know that I can set goals and crush them.

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Virat Singh

236,512 views • 2 years ago

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m0h

70,509 views • 1 month ago

I'm still picking my jaw off the floor with this MCP update: Postman will now automatically build an MCP server for an API. Automatically! You select your API and the requests you want to include, and Potman will generate a Zip file with everything you need. In collaboration with Postman, I recorded a video showing how I generated an MCP server for the Google Maps API. It's glorious! Also, and before I forget: You can now test any MCP server with your Postman application. They built MCP right in, so now you can: • Connect to an MCP server • List out all of the available tools • Test any of the tools This is a 10x boost for the MCP ecosystem. If you've tried the default MCP debugger, you'll understand how huge a deal it is that you can do all of that from Postman now. Go here to give this a try:

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Santiago

215,882 views • 1 year ago

We're currently rebranding APItoolkit to Monoscope (monoscope ). This is because the scope of the platform was beyond API monitoring (Even if it still can do that; 3rd party or own API monitoring). But Monoscope is now a general open telemetry vendor. So, anything that can be instrumented via OpenTelemetry can be monitored using Monoscope. You can also create all sorts of dashboards (and yes, you can use AI to make the charts). And you can have all your data be stored in your own s3 bucket (you own the data. We don't charge for retention), so you can query years of data via the platform. No extra cost. Let me know what you think. Cheers.

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Anthony Alaribe {···}

17,825 views • 9 months ago

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Santiago

230,594 views • 1 year ago

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Yasser

55,715 views • 1 year ago

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Box

227,348 views • 5 months ago

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kaize

137,488 views • 2 months ago

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Santiago

20,785 views • 2 months ago

DEMO:The 'Solana Smart Money Skynet System' , The goal is to create thousands of autonomously running AI 16ZDAOs for users. RT,PLEASE. We're starting by building an AI-driven address book of on-chain smart money, allowing AI to learn their behavioral patterns. In the future, this will enable automated on-chain operations tailored to user needs. P.S. In the DEMO, the AI had some incorrect understandings of the SOL balance of certain addresses; it's still in adversarial learning. Next week, we will launch the web client for MCP-0S's 'Solana Smart Money Skynet System' and open it for internal beta testing with a select group of users.#MCPOS

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LYRAOS

28,888 views • 1 year ago

I built a mobile app to check Paddle revenue (because they don't have one): 👉 - Use your Paddle API key (read-only and scoped) - Live data with beautiful and useful graphs built with native Swift UI. - Multi-account supported, unified revenue metrics. - Data stay on device, no server (api requests are sent directly from your phone) - Home widgets - I made it free to download on App Store (once it's approved) - Buy the source code for $19 and customize it however you want (save 5hrs of prompting if you try to do it yourself). Some interesting facts about this side project: - I vibe coded with 100% claude code remotely on my Mac Mini (with my AI assistant setup) in less than 24 hours. - I have read 0 line of code in this project and never opened Xcode myself. - My AI assistant designed the app with GPT Image 2, built the app with Swift UI, test it on simulator (via screenshots), send the test build to TestFlight for me to test, and invited me to the app store connect account so I can test on my phone, then the AI submitted the app to App Store and currently waiting for approval. - For the website, I ask it to come up with a domain name, I bought it via manually and give it access via Cloudflare API, the AI design and create a static website with GitHub, test it with lighthouse CLI, deploy via GitHub pages, config the domain DNS, deploy the website. - Then I sign up an account with Polar payment, create an API key and ask the AI to setup a store, add payment, link with the account, and add the payment to the website. The entire process happened in the last 24 hours with me only talking to the AI via Telegram. This is such a fun side project not only to create an app that I wish exists, but also to push the limit of what I can use AI for, and so far I'm very impressed. I'll create so much more apps! It feels like I have unlocked a super power.

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Tony Dinh

43,922 views • 2 months ago

This is a standard practice for almost all Tier-1 banking applications in Nigeria, and for some fintech applications I’ve previously performed pentests on. Client-side encryption isn’t a total waste, or a waste of compute, as some people have claimed, but rather a measure to protect against API tampering or API request/response manipulation between the client and the server when implemented properly. Even with HTTPS, attackers can capture a decrypted version of web or mobile API data in transit because the browser and the server establish a level of trust during the TLS handshake. Attackers can leverage this trust to capture & proxy already-decrypted traffic, tamper with it, and then forward it to the server. This allows them to override what the user interface or client is originally supposed to send and replace it with data of their choosing. That is why validation needs to be performed on both the client and the server side. To wrap up, encrypting API requests and responses makes it significantly harder for attackers to tamper with data, even if they capture the traffic, unless they have access to the encryption details (algorithm, encryption mode, key size, secret key, and initialization vector), assuming asymmetric encryption is used. In the demo below, you can see how I discovered additional parameters (balance, is_admin) in the API response, captured the registration API request, despite it being sent over HTTPS from the interface, added the discovered parameters, and successfully inflated my balance to 50 billion and also escalated my privileges to admin, and ultimately deleted the accounts of two live users/customers. In the second slide, I captured an API traffic of a bank app, and you can see how difficult the payloads are to read.

This is a standard practice for almost all Tier-1 banking applications in Nigeria, and for some fintech applications I’ve previously performed pentests on. Client-side encryption isn’t a total waste, or a waste of compute, as some people have claimed, but rather a measure to protect against API tampering or API request/response manipulation between the client and the server when implemented properly. Even with HTTPS, attackers can capture a decrypted version of web or mobile API data in transit because the browser and the server establish a level of trust during the TLS handshake. Attackers can leverage this trust to capture & proxy already-decrypted traffic, tamper with it, and then forward it to the server. This allows them to override what the user interface or client is originally supposed to send and replace it with data of their choosing. That is why validation needs to be performed on both the client and the server side. To wrap up, encrypting API requests and responses makes it significantly harder for attackers to tamper with data, even if they capture the traffic, unless they have access to the encryption details (algorithm, encryption mode, key size, secret key, and initialization vector), assuming asymmetric encryption is used. In the demo below, you can see how I discovered additional parameters (balance, is_admin) in the API response, captured the registration API request, despite it being sent over HTTPS from the interface, added the discovered parameters, and successfully inflated my balance to 50 billion and also escalated my privileges to admin, and ultimately deleted the accounts of two live users/customers. In the second slide, I captured an API traffic of a bank app, and you can see how difficult the payloads are to read.

Ghost St Badmus

217,475 views • 7 months ago

"I burned roughly $5,000 of API tokens in a few hours for $200. It's 100x subsidized. This is insanity" Kain on running 500+ agents to decompose an entire codebase on Claude Opus 4.8 "I set up my own personal account to test this on Opus 4.8. I know enough that I can come up with a task that's gonna burn a fuckload. In the course of four hours I used something like 200 million tokens and didn't hit any limits" "It was hundreds of agents, like 500 or 600 agents decomposing a codebase. It would have been somewhere on the order of $5,000 with API metered tokens, and I know how much tokens cost because that's where I live" "I ran this overnight multiple times. It's very possible I could have burned through $20,000 worth of API credits for $200. I knew it was subsidized, but it's subsidized to a level that's crazy. It's 100x subsidized"

"I burned roughly $5,000 of API tokens in a few hours for $200. It's 100x subsidized. This is insanity" Kain on running 500+ agents to decompose an entire codebase on Claude Opus 4.8 "I set up my own personal account to test this on Opus 4.8. I know enough that I can come up with a task that's gonna burn a fuckload. In the course of four hours I used something like 200 million tokens and didn't hit any limits" "It was hundreds of agents, like 500 or 600 agents decomposing a codebase. It would have been somewhere on the order of $5,000 with API metered tokens, and I know how much tokens cost because that's where I live" "I ran this overnight multiple times. It's very possible I could have burned through $20,000 worth of API credits for $200. I knew it was subsidized, but it's subsidized to a level that's crazy. It's 100x subsidized"

Laura Shin

85,115 views • 1 month ago

POLYMARKET BOTS ARE NOT BLACK BOXES -> Official Python client for Polymarket CLOB V2. If your pipeline is built in Python, this is probably the cleanest starting point: API creds, authenticated client, order flow, and direct CLOB interaction. -> A TypeScript library for Polymarket WebSocket data. Auto reconnect, dynamic subscriptions, book events, price changes, tick size changes, and last trade price. This is exactly the kind of repo you need for Step 1: recording the order book. -> Official Polymarket agent skills repo. This fits the “Now you can use AI” part perfectly: auth, order placement, market reads, live data streams, position management, and WebSocket patterns. Basically, the bridge between Polymarket data and AI agents. Not bad starter kit.

POLYMARKET BOTS ARE NOT BLACK BOXES -> Official Python client for Polymarket CLOB V2. If your pipeline is built in Python, this is probably the cleanest starting point: API creds, authenticated client, order flow, and direct CLOB interaction. -> A TypeScript library for Polymarket WebSocket data. Auto reconnect, dynamic subscriptions, book events, price changes, tick size changes, and last trade price. This is exactly the kind of repo you need for Step 1: recording the order book. -> Official Polymarket agent skills repo. This fits the “Now you can use AI” part perfectly: auth, order placement, market reads, live data streams, position management, and WebSocket patterns. Basically, the bridge between Polymarket data and AI agents. Not bad starter kit.

Couch

11,588 views • 3 months ago

AgentRouter is handing out $125 in FREE API credits for OPUS 4.8 > No card. > GitHub sign-in. > One API key for Opus 4.8 / Opus 4.7 / Sonnet 4.6 / GLM 5.1 The useful part is not “another model gateway.” It is that you can point coding tools and agents at one OpenAI-compatible base URL instead of juggling separate keys for Claude and GLM, and others. What you get: • $125 signup balance • one API key • OpenAI-compatible endpoints • chat, responses, messages, embeddings, images, audio, rerank endpoints listed • claimed support for Cursor, Claude Code, Hermes, and other agent tools The flow is simple: 1. go to AgentRouter (link in comment) 2. sign in or create an account 3. generate an API key in the console 4. copy the base URL 5. paste it into Cursor / Claude Code / your agent runtime 6. run a small test before moving anything serious Caveat: AgentRouter’s own site currently has a notice saying Claude-series service was recently hit by stability issues and large-scale Claude access was suspended. So don’t treat this as “guaranteed free Claude forever.” Treat it as $125 of free routing credits to test which models are live, how the latency feels, and whether the gateway is stable enough for your workflow. Still a very solid save if you build with agents. Most people burn paid API credits just testing configs. This gives you room to test first, then decide if it belongs in your stack.

AgentRouter is handing out $125 in FREE API credits for OPUS 4.8 > No card. > GitHub sign-in. > One API key for Opus 4.8 / Opus 4.7 / Sonnet 4.6 / GLM 5.1 The useful part is not “another model gateway.” It is that you can point coding tools and agents at one OpenAI-compatible base URL instead of juggling separate keys for Claude and GLM, and others. What you get: • $125 signup balance • one API key • OpenAI-compatible endpoints • chat, responses, messages, embeddings, images, audio, rerank endpoints listed • claimed support for Cursor, Claude Code, Hermes, and other agent tools The flow is simple: 1. go to AgentRouter (link in comment) 2. sign in or create an account 3. generate an API key in the console 4. copy the base URL 5. paste it into Cursor / Claude Code / your agent runtime 6. run a small test before moving anything serious Caveat: AgentRouter’s own site currently has a notice saying Claude-series service was recently hit by stability issues and large-scale Claude access was suspended. So don’t treat this as “guaranteed free Claude forever.” Treat it as $125 of free routing credits to test which models are live, how the latency feels, and whether the gateway is stable enough for your workflow. Still a very solid save if you build with agents. Most people burn paid API credits just testing configs. This gives you room to test first, then decide if it belongs in your stack.

kocer

24,905 views • 1 month ago

My agent is now paying for its own data. No API key. No account. No credit card. Check the video I recorded. This uses the x402 open protocol built by Coinbase, along with a simple skill. This is an open protocol governed by the Linux Foundation. To complete a goal, an agent can now search for an actor on the Apify Store, pay for it, and use it without any human intervention. The way it works is pretty simple: 1. Your agent finds an Actor it wants to use 2. It sends a request 3. The Actor sends back an HTTP 402 "Payment Required" response 4. Agent authorizes payment from a wallet in USDC on Base 5. The Actor runs 6. User receives the result The model is pay-as-you-go: the agent authorizes a spending ceiling, pays only for usage, and the remaining balance is automatically settled. This brings an entire marketplace of AI tools into the agentic economy. Here is the skill you need. Add it to your agent, and it will take care of everything for you: If you want to know how this works, including what you can do with $1, read this post: Thanks to the Apify team for partnering with me on this post.

My agent is now paying for its own data. No API key. No account. No credit card. Check the video I recorded. This uses the x402 open protocol built by Coinbase, along with a simple skill. This is an open protocol governed by the Linux Foundation. To complete a goal, an agent can now search for an actor on the Apify Store, pay for it, and use it without any human intervention. The way it works is pretty simple: 1. Your agent finds an Actor it wants to use 2. It sends a request 3. The Actor sends back an HTTP 402 "Payment Required" response 4. Agent authorizes payment from a wallet in USDC on Base 5. The Actor runs 6. User receives the result The model is pay-as-you-go: the agent authorizes a spending ceiling, pays only for usage, and the remaining balance is automatically settled. This brings an entire marketplace of AI tools into the agentic economy. Here is the skill you need. Add it to your agent, and it will take care of everything for you: If you want to know how this works, including what you can do with $1, read this post: Thanks to the Apify team for partnering with me on this post.

Santiago

26,589 views • 1 month ago

An AI agent can now register its on-chain identity, pay for API calls, and deploy an ERC-20 token from the terminal. No browser. No API key. No human approval loop. Today we launch the Brickken CLI: a command-line interface for agentic transaction workflows. The developer journey is direct: CLI → x402 → ERC-8004 → Token Deploy What this means in practice: • A developer or the AI agent installs the CLI. • The agent pays for Brickken API calls through x402. • The agent registers its identity through ERC-8004. • The agent deploys and manages an ERC-20 token. Together, the stack gives agents three things they usually lack: a way to pay, a way to prove who they are, and a way to execute token operations without leaving the terminal. • x402 handles payment. • ERC-8004 handles agent identity. • Token Deploy handles ERC-20 execution. This is live today. Developers can now move from agent setup to payment, identity registration, and token deployment in one terminal workflow. Start here: Watch the demo. Run the commands. Deploy from the terminal.

An AI agent can now register its on-chain identity, pay for API calls, and deploy an ERC-20 token from the terminal. No browser. No API key. No human approval loop. Today we launch the Brickken CLI: a command-line interface for agentic transaction workflows. The developer journey is direct: CLI → x402 → ERC-8004 → Token Deploy What this means in practice: • A developer or the AI agent installs the CLI. • The agent pays for Brickken API calls through x402. • The agent registers its identity through ERC-8004. • The agent deploys and manages an ERC-20 token. Together, the stack gives agents three things they usually lack: a way to pay, a way to prove who they are, and a way to execute token operations without leaving the terminal. • x402 handles payment. • ERC-8004 handles agent identity. • Token Deploy handles ERC-20 execution. This is live today. Developers can now move from agent setup to payment, identity registration, and token deployment in one terminal workflow. Start here: Watch the demo. Run the commands. Deploy from the terminal.

Brickken

14,429 views • 1 month ago

I've never recorded a video announcement before. But after 15 years of working in AI and 1.5 years heads down building Cambrian Network 🪴, I wanted to share this news myself. I'm proud to announce the public launch of the Cambrian API, which you can try free on In 2024, while building an AI copilot for trading, I became convinced that the future of finance would be increasingly operated by agents. I also realized that existing data solutions were far from meeting the needs of a burgeoning industry called agentic finance. So I assembled a team of data, infrastructure, and finance veterans, earned support from a16z crypto Polychain Franklin Templeton Digital Assets and many other amazing investors, and embarked on a mission to build the world's financial intelligence layer. Today, the Cambrian API is out of beta. It's the best source of onchain and offchain signal for AI agents and institutions to make winning financial decisions, such as: - Smarter trading strategies - Automated yield-maximization - Social sentiment-based trades - Risk analyses & much more Start using it for free and scale as your needs grow.

I've never recorded a video announcement before. But after 15 years of working in AI and 1.5 years heads down building Cambrian Network 🪴, I wanted to share this news myself. I'm proud to announce the public launch of the Cambrian API, which you can try free on In 2024, while building an AI copilot for trading, I became convinced that the future of finance would be increasingly operated by agents. I also realized that existing data solutions were far from meeting the needs of a burgeoning industry called agentic finance. So I assembled a team of data, infrastructure, and finance veterans, earned support from a16z crypto Polychain Franklin Templeton Digital Assets and many other amazing investors, and embarked on a mission to build the world's financial intelligence layer. Today, the Cambrian API is out of beta. It's the best source of onchain and offchain signal for AI agents and institutions to make winning financial decisions, such as: - Smarter trading strategies - Automated yield-maximization - Social sentiment-based trades - Risk analyses & much more Start using it for free and scale as your needs grow.

Sam Green

27,633 views • 2 days ago

How to use 50+ API keys (models) for FREE on OpenClaw API??? - go to - login or register your account - click on "more models" - click on "use case" and select what you need it for - choose the model and open it - click on "view code" → "Generate API key" many models don't allow direct deploy, so use the "view code" button to generate API access basically Nvidia NIM gives you the ability to test almost any model from their list for FREE some of them are not worse than GPT 5.2 or Claude Opus 4.6, some might even perform better depending on the task how to understand if a model is efficient and compare it with others??? - go to - type the model name in search - click on "benchmarks" - you’ll see performance tests and rankings this way you can easily compare free models with paid ones of course there are RPM limits, on many models it’s around ~40 requests per minute each model is different, after generating the API key, RPM limits are shown in the top-right corner nothing stops you from using them, many work perfectly fine, super solid option for first tests and for learning OpenClaw or any other system where you need an AI API model

How to use 50+ API keys (models) for FREE on OpenClaw API??? - go to - login or register your account - click on "more models" - click on "use case" and select what you need it for - choose the model and open it - click on "view code" → "Generate API key" many models don't allow direct deploy, so use the "view code" button to generate API access basically Nvidia NIM gives you the ability to test almost any model from their list for FREE some of them are not worse than GPT 5.2 or Claude Opus 4.6, some might even perform better depending on the task how to understand if a model is efficient and compare it with others??? - go to - type the model name in search - click on "benchmarks" - you’ll see performance tests and rankings this way you can easily compare free models with paid ones of course there are RPM limits, on many models it’s around ~40 requests per minute each model is different, after generating the API key, RPM limits are shown in the top-right corner nothing stops you from using them, many work perfectly fine, super solid option for first tests and for learning OpenClaw or any other system where you need an AI API model

Ronin

58,846 views • 5 months ago