Octagon Investment Research logo

Octagon Investment Research

Organization
octagonai

A free MCP server to analyze and extract insights from public filings, earnings transcripts, financial metrics, stock market data, private market transactions, and deep web-based research within Claude Desktop and other popular MCP clients.

Publisheroctagonai
Repositoryoctagon-mcp-server
LanguageTypeScript
Forks
19
Stars
122
Available tools
0
Transport typestdio
Categories
LicenseMIT
Links
  • Connect tools to AI workflows

    Octagon Investment Research exposes MCP capabilities that can be used by compatible AI clients and agents.

  • 0 available tools

    Browse the callable actions below, including names and descriptions when provided by the server.

  • Ready-to-copy setup

    Use the installation snippets to configure this server in your preferred MCP client.

  • Open source signals

    122 stars and 19 forks from the linked repository.

Octagon: MCP for Market Data

smithery badge

Favicon 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.

Demo

Tools

octagon-agent orchestrates broad market intelligence analysis

  • Public market insights (SEC filings, transcripts, financials, stock data)
  • Private market insights (companies, funding rounds, deals, debt, investors)

octagon-deep-research-agent for comprehensive deep research

  • Multi-source synthesis for investment research questions
  • Best for up-to-date, cross-source thematic analysis

✅ Prediction market research tooling

  • octagon-prediction-markets-agent for Kalshi event research reports
  • prediction_markets_history for structured historical market data retrieval

Get Your Octagon API Key

To use Octagon MCP, you need to:

  1. Sign up for a free account at Octagon
  2. After logging in, from left menu, navigate to API Keys
  3. Generate a new API key
  4. Use this API key in your configuration as the OCTAGON_API_KEY value

Prerequisites

Before installing or running Octagon MCP, you need to have npx (which comes with Node.js and npm) installed on your system.

Mac (macOS)

  1. Install Homebrew (if you don't have it):

    bash
    /bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"
  2. Install Node.js (includes npm and npx):

    bash
    brew install node

    This will install the latest version of Node.js, npm, and npx.

  3. Verify installation:

    bash
    node -v
    npm -v
    npx -v

Windows

  1. Download the Node.js installer:
  2. Run the installer and follow the prompts. This will install Node.js, npm, and npx.
  3. Verify installation: Open Command Prompt and run:
    cmd
    node -v
    npm -v
    npx -v

If you see version numbers for all three, you are ready to proceed with the installation steps below.

Installation

Running on Claude Desktop

To configure Octagon MCP for Claude Desktop:

  1. Open Claude Desktop
  2. Go to Settings > Developer > Edit Config
  3. Add the following to your claude_desktop_config.json (Replace your-octagon-api-key with your Octagon API key):
json
{
  "mcpServers": {
    "octagon-mcp-server": {
      "command": "npx",
      "args": ["-y", "octagon-mcp@latest"],
      "env": {
        "OCTAGON_API_KEY": "YOUR_API_KEY_HERE"
      }
    }
  }
}
  1. Restart Claude for the changes to take effect

Running on Cursor

Configuring Cursor Desktop 🖥️ Note: Requires Cursor version 0.45.6+

To configure Octagon MCP in Cursor:

  1. Open Cursor Settings
  2. Go to Features > MCP Servers
  3. Click "+ Add New MCP Server"
  4. Enter the following:
    • Name: "octagon-mcp" (or your preferred name)
    • Type: "command"
    • Command: env OCTAGON_API_KEY=your-octagon-api-key npx -y octagon-mcp

If 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.

Running with npx

bash
env OCTAGON_API_KEY=your_octagon_api_key npx -y octagon-mcp

Manual Installation

bash
npm install -g octagon-mcp

Documentation

For comprehensive documentation on using Octagon agents, please visit our official documentation at: https://docs.octagonagents.com

The documentation includes:

  • Detailed API references
  • Agent-specific query guidelines
  • Examples and use cases
  • Best practices for investment research

For the latest hosted MCP client setup guide, see:

Available Tools

The MCP server currently exposes the following tools:

octagon-agent

Orchestrates 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:

  1. stored conversation for MCP transport session identity, when the transport actually provides it
  2. stored conversation for the server-managed default stdio session
  3. explicit conversation can still override the active session conversation for that call

This 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:

  1. First call: send only prompt
  2. Let the MCP host preserve transport session continuity or rely on the default stdio session
  3. Second call: either
    • send the new prompt in the same MCP session, or
    • keep using the same stdio MCP process, or
    • explicitly pass the previous conversation

Transport 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:

  • MCP session identity controls server-side continuity across tool calls
  • Octagon conversation controls the active Octagon thread inside that session

The MCP result keeps the answer in content, and also returns structured metadata for orchestrators in structuredContent:

json
{
  "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:

json
{
  "prompt": "AAPL",
  "conversation": "conv_123"
}

New visible chat example:

json
{
  "prompt": "Analyze Apple",
  "newConversation": true
}

Explicit refresh example:

json
{
  "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 conversation
  • other MCP tools: stateless and may run without session continuity

Example:

text
Compare NVIDIA and AMD on latest quarterly revenue growth, margins, and management commentary.

More examples:

  • "What were Amazon's revenue and net income figures in Q4 2023?"
  • "Analyze Tesla's R&D spending trends over the last 3 years."
  • "What guidance did NVIDIA's CEO provide regarding AI chip demand in their latest earnings call?"
  • "Compare the price-to-earnings, price-to-sales, and EV/EBITDA ratios for the top 5 semiconductor companies."
  • "What was Anthropic's latest funding round size, valuation, and key investors?"
  • "How many investments did Andreessen Horowitz make in AI startups in the last 12 months?"

octagon-deep-research-agent

Performs comprehensive multi-source deep research and synthesis.

Parameters

  • prompt (string, required): natural language research request.

Example:

text
Research the impact of lower interest rates on late-stage private software valuations over the next 12 months.

More examples:

  • "Extract all data fields from zillow.com/san-francisco-ca/"
  • "Research the financial impact of Apple's privacy changes on digital advertising companies' revenue and margins"
  • "Retrieve historical Bitcoin price data from 2023 and analyze the price volatility trends"
  • "Analyze the competitive dynamics in the EV charging infrastructure market"

octagon-prediction-markets-agent

Generates research reports for Kalshi prediction market events.

Parameters

  • prompt (string, required): natural language research request.
  • cache (boolean, optional): controls agent variant routing.
    • omitted: prediction-markets-agent
    • false: prediction-markets-agent:refresh
    • true: prediction-markets-agent:cache

Example:

text
Generate a report for the Kalshi market https://kalshi.com/markets/kxbtcy/btc-price-range-eoy/kxbtcy-27jan0100

prediction_markets_history

Fetches 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:

text
Fetch historical data for the Kalshi event https://kalshi.com/markets/kxbtcy/btc-price-range-eoy/kxbtcy-27jan0100

Troubleshooting

  1. API Key Issues: Ensure your Octagon API key is correctly set in the environment or config file.
  2. Connection Issues: Make sure the connectivity to the Octagon API is working properly.
  3. Rate Limiting: If you encounter rate limiting errors, reduce the frequency of your requests.

License

MIT

Individual Specialized MCP Servers

While this server provides comprehensive market intelligence combining all our specialized agents, you can also use our individual MCP servers for specific use cases:

Public Market Data Servers

Private Market Data Servers

Research Tools


⭐ Star this repo if you find it helpful!

Installation

TypingMind
Prerequisites:

Node.js 18+

{
  "mcpServers": {
    "octagon-mcp-server": {
      "command": "npx",
      "args": [
        "-y",
        "octagon-mcp@latest"
      ],
      "env": {
        "OCTAGON_API_KEY": "YOUR_API_KEY_HERE"
      }
    }
  }
}

Use Octagon Investment Research MCP with multiple AI models

TypingMind connects MCP tools at the workspace level, so once Octagon Investment Research is connected, you can use it with different AI models in TypingMind instead of setting it up separately for each model. This MCP runs locally through the TypingMind MCP connector on your device.

Setup guide to use the local connector

Use this when the MCP server needs access to local files, apps, or private resources on your computer.

1

Open the MCP settings

In TypingMind, go to Settings, Advanced Settings, then Model Context Protocol and choose Setup Connector.

  1. Open TypingMind in your browser.
  2. Click the Settings icon.
  3. Go to Advanced Settings.
  4. Open the Model Context Protocol section.
  5. Click Setup Connector and choose This Device.
TypingMind MCP connector setup screen with This Device selected
2

Run the connector command

Choose This Device, copy the command from TypingMind, and run it in Terminal. Keep the process running while you use MCP.

  1. Copy the setup command shown by TypingMind.
  2. Open Terminal on macOS or Windows Terminal on Windows.
  3. Paste and run the command.
  4. Approve the package install if Terminal asks you to proceed.
  5. Keep the Terminal window running while using MCP tools.
3

Add Octagon Investment Research as a server

When the connector status is Ready, click Edit Servers and paste the MCP server configuration.

  1. Wait until the connector status shows Ready.
  2. Click Edit Servers.
  3. Paste the Octagon Investment Research MCP server configuration.
  4. Save the server list.
  5. Refresh if you want to confirm the connector is still ready.
TypingMind MCP settings showing active server and Edit Servers button
{
  "mcpServers": {
    "octagon-investment-research": {
      "command": "npx",
      "args": [
        "-y",
        "octagon-mcp"
      ]
    }
  }
}
4

Use it across models

Save the server list, open Plugins, enable the Octagon Investment Research MCP tools, then select any supported AI model in TypingMind and use the tools in chat or assign them to an AI agent.

  1. Open the Plugins page in TypingMind.
  2. Enable the Octagon Investment Research MCP tools.
  3. Start a chat and choose the AI model you want to use.
  4. Use the MCP tools in chat or assign them to an AI agent.
  5. Switch to another AI model whenever needed without reconnecting MCP.
TypingMind chat using enabled MCP tools with a selected AI model
Can you use Octagon Investment Research to help me with this task?
Octagon Investment Research
Sure. I read it.
Here is what I found using Octagon Investment Research.

Frequently asked questions

What is the Octagon Investment Research MCP server used for?

Octagon Investment Research is an MCP server that lets compatible AI clients connect to external tools and context. In TypingMind, you can add this MCP server once and make its tools available in your AI workspace.

Can I use Octagon Investment Research MCP with multiple AI models in TypingMind?

Yes. TypingMind connects MCP tools at the workspace level, so you can use Octagon Investment Research with different AI models such as Claude, ChatGPT, Gemini, or other models you have configured in TypingMind without setting up the MCP server separately for each model.

Why use Octagon Investment Research MCP with TypingMind?

TypingMind is one of the best frontends for LLM chat because it brings multiple AI models, prompts, plugins, AI agents, API keys, and MCP tools into one workspace. With Octagon Investment Research connected, you can use its MCP tools across your preferred models while keeping your chat workflow organized in TypingMind.

How do I connect Octagon Investment Research MCP to TypingMind?

Octagon Investment Research runs through the TypingMind local MCP connector. This is best when the MCP server needs access to local files, desktop apps, command-line tools, or private resources on your computer.

What tools does Octagon Investment Research MCP provide in TypingMind?

Octagon Investment Research exposes MCP capabilities that can be enabled from the TypingMind Plugins page and used in chat or assigned to AI agents.

Do I need to share my API keys with TypingMind to use Octagon Investment Research MCP?

No. TypingMind is local-first and lets you keep your model providers, API keys, prompts, and MCP configuration under your control. If Octagon Investment Research requires authentication, add the required headers, OAuth settings, or local configuration for that MCP server when you create the connection.

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