{"repo":"featureform/enrichmcp","free":true,"listed":false,"github":"https://github.com/featureform/enrichmcp","clone":"git clone https://github.com/featureform/enrichmcp.git","description":"EnrichMCP is a python framework for building data driven MCP servers","language":"Python","stars":644,"topics":[],"license":"Apache-2.0","category":"mcp-servers","readme_excerpt":"EnrichMCP The ORM for AI Agents - Turn your data model into a semantic MCP layer EnrichMCP is a Python framework that helps AI agents understand and navigate your data. Built on MCP (Model Context Protocol), it adds a semantic layer that turns your data model into typed, discoverable tools - like an ORM for AI. What is EnrichMCP? Think of it as SQLAlchemy for AI agents. EnrichMCP automatically: - Generates typed tools from your data models - Handles relationships between entities (users → orders → products) - Provides schema discovery so AI agents understand your data structure - Validates all inputs/outputs with Pydantic models - Works with any backend - databases, APIs, or custom logic Installation Show Me Code Option 1: I Have SQLAlchemy Models (30 seconds) Transform your existing SQLAlchemy models into an AI-navigable API: AI agents can now: - explore data model() - understand your entire schema - list users(status='active') - query with filters - get user(id=123) - fetch specific records - Navigate relationships: user.orders → order.user Option 2: I Have REST APIs (2 minutes) Wrap your existing APIs with semantic understanding: Option 3: I Want Full Control (5 minutes) Build a complete data layer with custom logic: Key Features 🔍 Automatic Schema Discovery AI agents explore your entire data model with one call: 🔗 Relationship Navigation Define relationships once, AI agents traverse naturally: 🛡️ Type Safety & Validation Full Pydantic validation on every interaction: d","default_branch":null,"files":null,"tree":[],"storefront":"/r/featureform","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/featureform/enrichmcp/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}