MCP Tools
Molecule MCP Server Documentation
Overview
The Molecule MCP (Model Context Protocol) server enables AI assistants to access DeSci ecosystem data through natural language. Users can query AI assistants like Claude with questions like "What IPTs are available?" to receive real-time responses.
What is MCP?
Model Context Protocol is an open standard that allows AI assistants to utilize external tools, enabling access to current data from sources like Molecule's datasets.
MCP Server Functionality
The MCP server bridges AI assistants and Molecule Protocol data. It allows AI to fetch real data about IPTs, prices, and project activity, rather than just relying on pre-trained knowledge.
Example Interaction
Query: "What's the price history for HAIR?"
Process:
AI Assistant interprets the request.
Selects the appropriate tool.
Calls the Molecule MCP server at
https://molecule-mcp.vercel.app/mcp.
Data Sources
The MCP server pulls information from various resources like:
Molecule API (GraphQL)
Sanity CMS (Categories)
GeckoTerminal (Price Data)
Quick Start Guide
Claude Desktop Integration
To enable Molecule tools in Claude Desktop:
macOS: Add to
~/Library/Application Support/Claude/claude_desktop_config.jsonWindows: Add to
%APPDATA%\Claude\claude_desktop_config.json
Restart Claude Desktop after saving.
Claude Code Integration
For CLI using Claude Code, add .mcp.json to your project root:
Other MCP Clients
Connect using Streamable HTTP transport:
Example Conversations
Ecosystem Overview: "What's happening in the Molecule ecosystem?"
Project Deep Dive: "I'm interested in the HAIR project. What can you tell me?"
Price Analysis: "How has VITA-FAST performed over the last month?"
Self-Hosting
For private deployments or custom configurations:
Requirements
Node.js 18 or higher
Vercel account or any Node.js platform
Molecule API key
Deploy Steps
Request access to the MCP server source from the Molecule team (the repository is not publicly listed).
Install dependencies:
Deploy to Vercel:
Add environment variables in Vercel under Settings.
Local Development
Start with:
Caching
The server caches upstream responses in Redis for a few minutes, enhancing performance and abiding by upstream limits — expect data freshness in the minutes range rather than real-time.
Rate Limits
The public endpoint is rate-limited. Deploy your own instance for heavy or latency-sensitive workloads.
Programmatic Integration
For AI applications requiring Molecule data, connect to the MCP endpoint directly. Any MCP-compatible client works — the example below uses the Vercel AI SDK's MCP client.
Troubleshooting
Ensure configuration file syntax is valid.
First request may be slower; consider using Redis for caching.
Deploy your own instance if facing rate limit errors.
Resources
Public Endpoint: https://molecule-mcp.vercel.app/mcp
MCP Specification: https://modelcontextprotocol.io
Source Code & API Key Request: Contact the Molecule team.
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