Octagon AI Agents to integrate private and public market data
Claude Desktop config.json'a ekle
{
"mcpServers": {
"octagonai-octagon-mcp-server": {
"command": "node",
"args": [
"~/.mcp/octagon-mcp-server/index.js"
]
}
}
} Kaynak kodu al ve yerel olarak çalıştır
git clone https://github.com/OctagonAI/octagon-mcp-server.git ~/.mcp/octagon-mcp-server
cd ~/.mcp/octagon-mcp-server The Octagon MCP server provides specialized AI-powered financial research and analysis by integrating with the Octagon Market Intelligence API, enabling users to analyze and extract insights from public filings, earnings calls, financial metrics, private market transactions, and prediction market events within Claude Desktop and other popular MCP clients.
✅ octagon-agent orchestrates broad market intelligence analysis
✅ octagon-deep-research-agent for comprehensive deep research
✅ Prediction market research tooling
octagon-prediction-markets-agent for Kalshi event research reportsprediction_markets_history for structured historical market data retrieval✅ Live Octagon documentation access
octagon-docs-search, octagon-docs-read, octagon-docs-list, and octagon-docs-refreshoctagon-docs://catalog, octagon-docs://status, and octagon-docs://page/{target}To use Octagon MCP, you need to:
OCTAGON_API_KEY valueBefore installing or running Octagon MCP, you need to have npx (which comes with Node.js and npm) installed on your system.
Install Homebrew (if you don’t have it):
/bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"
Install Node.js (includes npm and npx):
brew install node
This will install the latest version of Node.js, npm, and npx.
Verify installation:
node -v
npm -v
npx -v
node -v
npm -v
npx -v
If you see version numbers for all three, you are ready to proceed with the installation steps below.
To configure Octagon MCP for Claude Desktop:
claude_desktop_config.json (Replace your-octagon-api-key with your Octagon API key):{
"mcpServers": {
"octagon-mcp-server": {
"command": "npx",
"args": ["-y", "octagon-mcp@latest"],
"env": {
"OCTAGON_API_KEY": "YOUR_API_KEY_HERE"
}
}
}
}
Configuring Cursor Desktop 🖥️ Note: Requires Cursor version 0.45.6+
To configure Octagon MCP in Cursor:
env OCTAGON_API_KEY=your-octagon-api-key npx -y octagon-mcpIf you are using Windows and are running into issues, try
cmd /c "set OCTAGON_API_KEY=your-octagon-api-key && npx -y octagon-mcp"
Replace your-octagon-api-key with your Octagon API key.
After adding, refresh the MCP server list to see the new tools. The Composer Agent will automatically use Octagon MCP when appropriate, but you can explicitly request it by describing your investment research needs. Access the Composer via Command+L (Mac), select “Agent” next to the submit button, and enter your query.
env OCTAGON_API_KEY=your_octagon_api_key npx -y octagon-mcp
npm install -g octagon-mcp
For comprehensive documentation on using Octagon agents, please visit our official documentation at: https://octagonai.co/docs/
The documentation includes:
For the latest hosted MCP client setup guide, see:
This MCP server also exposes the live docs corpus directly to MCP clients. Documentation access is fetched from the public Octagon docs LLM entry point at https://octagonai.co/docs/llms.txt; it does not use or transmit OCTAGON_API_KEY.
The MCP server currently exposes the following tools:
These tools expose live Octagon docs inside the MCP session. They work even before OCTAGON_API_KEY is configured, which makes them useful for setup, troubleshooting, and discovering the right Octagon agent or API workflow.
octagon-docs-listLists live docs sections and pages from the Octagon docs corpus.
Parameters
section (string, optional): filter by docs section.source (docs, site, or all, optional): defaults to the docs corpus.limit (number, optional): maximum entries to return.octagon-docs-searchSearches the Octagon API, agent, MCP, and plugin docs with source URLs and optional snippets.
Parameters
query (string, required): search query.section (string, optional): filter by docs section.source (docs, site, or all, optional): defaults to the docs corpus.limit (number, optional): maximum results to return.includeSnippets (boolean, optional): include matched snippets in results.Example:
Search Octagon docs for Claude plugin connector setup.
octagon-docs-readReads one docs page or section as Markdown by title, URL, path, or catalog id.
Parameters
target (string, required): docs title, URL, path, or catalog id.source (docs, site, or all, optional): defaults to the docs corpus.maxChars (number, optional): maximum Markdown characters to return.preferCachedContent (boolean, optional): use the indexed docs corpus when available.Example:
Read the Octagon MCP server guide.
octagon-docs-refreshRefreshes the in-memory docs catalog from the live LLM-friendly docs endpoints.
Parameters
includeSite (boolean, optional): also refresh the broader https://octagonai.co/llms.txt site index.Clients that support MCP resources can also browse:
octagon-docs://catalog: normalized live docs catalog.octagon-docs://status: cache state, source endpoints, and refresh metadata.octagon-docs://page/{target}: one docs page or section as Markdown.octagon-agentOrchestrates public and private market intelligence analysis.
Parameters
prompt (string, required): natural language research request.conversation (string, optional): existing Octagon conversation ID to continue a prior octagon-agent thread. Omit this on the first turn.newConversation (boolean, optional): if true, starts a fresh Octagon thread for the active session/thread anchor. Recommended for the first turn of a brand new visible chat in top-layer hosts such as Claude Desktop.Threaded usage
octagon-agent is the only MCP tool that forwards Octagon conversation threading. It is a stateful tool and expects session continuity. The MCP resolves session/thread state in this order:
stdio sessionconversation can still override the active session conversation for that callThis package currently runs as a stdio MCP server. In stdio mode, the server automatically establishes a process-local session for continuity across calls. Most local hosts such as Claude Desktop or Cursor can therefore use octagon-agent without supplying any extra threading fields for basic follow-up behavior.
When a top-layer host knows a call is the first turn of a new visible chat, it should pass newConversation: true. That explicitly clears any stored Octagon thread for the active MCP session anchor before the call, which prevents stale continuity when a stdio host reuses the same long-lived MCP process across multiple visible chats.
This means you can use any of these patterns:
promptprompt in the same MCP session, orconversationTransport session identity is the canonical continuity primitive for standards-compliant stateful MCP transports. For local stdio usage, the server-managed process session provides default continuity.
Session identity and Octagon conversation identity are different concepts:
conversation controls the active Octagon thread inside that sessionThe MCP result keeps the answer in content, and also returns structured metadata for orchestrators in structuredContent:
{
"model": "octagon-agent",
"text": "Which stock would you like the latest price for?",
"conversation": "conv_123",
"responseId": "resp_123",
"followUp": {
"required": true,
"inputTemplate": "<ticker or company name>",
"instructions": "Reply with just the missing detail and reuse the conversation value from this response."
}
}
Explicit carry-forward example:
{
"prompt": "AAPL",
"conversation": "conv_123"
}
New visible chat example:
{
"prompt": "Analyze Apple",
"newConversation": true
}
Explicit refresh example:
{
"prompt": "Start a fresh Octagon thread for this chat",
"newConversation": true
}
Stateful tool policy
octagon-agent: stateful, uses a usable continuity anchor. In stdio hosts, that defaults to the server-managed process session unless you provide explicit conversationExample:
Compare NVIDIA and AMD on latest quarterly revenue growth, margins, and management commentary.
More examples:
octagon-deep-research-agentPerforms comprehensive multi-source deep research and synthesis.
Parameters
prompt (string, required): natural language research request.Example:
Research the impact of lower interest rates on late-stage private software valuations over the next 12 months.
More examples:
octagon-prediction-markets-agentGenerates research reports for Kalshi prediction market events.
Parameters
prompt (string, required): natural language research request.cache (boolean, optional): controls agent variant routing.
prediction-markets-agentfalse: prediction-markets-agent:refreshtrue: prediction-markets-agent:cacheExample:
Generate a report for the Kalshi market https://kalshi.com/markets/kxbtcy/btc-price-range-eoy/kxbtcy-27jan0100
prediction_markets_historyFetches historical data for a prediction market event ticker with optional pagination and time filters.
Parameters
event_ticker (string, required)limit (number, optional)cursor (string, optional)captured_from (string, optional)captured_to (string, optional)include_analysis (boolean, optional; when true, requests analysis columns)Example:
Fetch historical data for the Kalshi event https://kalshi.com/markets/kxbtcy/btc-price-range-eoy/kxbtcy-27jan0100
MIT
While this server provides comprehensive market intelligence combining all our specialized agents, you can also use our individual MCP servers for specific use cases:
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