sec-ai: SEC EDGAR

sec-finance-ai MCP server

AI-powered SEC EDGAR integration: 23 tools on the official sec.gov APIs, in one Python file.

🚀 Thousands of downloads on ClawHub and OpenWebUI

10-K, 10-Q, 8-K, 20-F and proxy filings, the full text of any filing read in pages or searched, XBRL company facts and cross-company rankings, Form 4 insider trades, 13D/13G ownership, 13F fund portfolios, IPOs, and full-text search of every filing since 2001.

Install

Needs uv. No API key.

Claude Code:

claude mcp add sec-ai -e SEC_USER_AGENT="Your Name you@example.com" -- uvx sec-finance-ai@latest

VS Code:

code --add-mcp '{"name":"sec-ai","type":"stdio","command":"uvx","args":["sec-finance-ai@latest"],"env":{"SEC_USER_AGENT":"Your Name you@example.com"}}'

Claude Desktop, Cursor, Windsurf and other clients, in the client's MCP config file:

{

"mcpServers": { "sec-ai": { "command": "uvx", "args": [ "sec-finance-ai@latest" ], "env": { "SEC_USER_AGENT": "Your Name you@example.com" } } } }

@latest picks up new releases when the client starts. Without uv: pip install sec-finance-ai, then use "command": "sec-finance-ai" with no args.

SEC_USER_AGENT is the name and e-mail the SEC asks programs to send. If it is not set, a default is sent.

Listed in the MCP Registry as io.github.lkcair/sec-ai. Every tool is read-only.

Agent frameworks

The server runs over stdio with uvx sec-finance-ai@latest, so any framework with MCP support can load all its tools.

SEC_USER_AGENT is optional. MCP starts the server with a minimal environment, so pass it as shown; **os.environ keeps PATH, so uvx is found.

LangChain: pip install "langchain[mcp]" langchain-anthropic

import asyncio

import os from langchain.agents import create_agent from langchain.mcp import MCPAdapter

async def main(): config = {"mcpServers": {"sec-ai": { "command": "uvx", "args": ["sec-finance-ai@latest"], "env": {**os.environ, "SEC_USER_AGENT": "Your Name you@example.com"}, # optional }}} async with MCPAdapter(config) as adapter: tools = await adapter.list_tools() agent = create_agent("claude-sonnet-5", tools) result = await agent.ainvoke({"messages": [{"role": "user", "content": "What does Apple's latest 10-K say about Greater China?"}]}) print(result"messages".content)

asyncio.run(main())

Google ADK: pip install "google-adk[mcp]"

import os

from google.adk.agents import LlmAgent from google.adk.tools.mcp_tool import McpToolset from google.adk.tools.mcp_tool.mcp_session_manager import StdioConnectionParams from mcp import StdioServerParameters

root_agent = LlmAgent( model="gemini-flash-latest", name="sec_ai", instruction="Answer with the sec-ai tools.", tools=[McpToolset(connection_params=StdioConnectionParams( server_params=StdioServerParameters( command="uvx", args=["sec-finance-ai@latest"], env={**os.environ, "SEC_USER_AGENT": "Your Name you@example.com"}, # optional ), timeout=60, ))], )

Strands Agents: pip install strands-agents

import os

from mcp import stdio_client, StdioServerParameters from strands import Agent from strands.tools.mcp import MCPClient

sec_ai = MCPClient(lambda: stdio_client(StdioServerParameters( command="uvx", args=["sec-finance-ai@latest"], env={**os.environ, "SEC_USER_AGENT": "Your Name you@example.com"}, # optional ))) agent = Agent(tools=[sec_ai]) agent("What does Apple's latest 10-K say about Greater China?")

Example questions

• What does Apple's latest 10-K say about Greater China?
• What are Berkshire Hathaway's top holdings in its latest 13F?
• Find every 8-K this year that mentions 'going concern'.
• Which companies had the highest revenue in 2024?

MCP tools (22)

Filings

Reading inside a filing

Search

Ownership and insiders

Financial data (XBRL)

Utility

License

MIT. All data comes from public SEC EDGAR databases. Not affiliated with the U.S. Securities and Exchange Commission.