API2MCP

Universal API to MCP Server Converter with LangGraph Orchestration

Convert any REST/GraphQL API into a fully functional MCP (Model Context Protocol) server, and orchestrate intelligent multi-API workflows using LangGraph.

Features

• 🔄 Automatic Conversion: OpenAPI, GraphQL, Postman → MCP Server
• 🔐 Enterprise Security: OAuth 2.0, API keys, secret management
• 🧠 Intelligent Orchestration: LangGraph-powered multi-API workflows
• 💾 State Persistence: Checkpoint-based workflow recovery
• 🔌 Extensible: Plugin architecture for custom integrations

Quick Start

# Install
pip install api2mcp

# Generate MCP server from OpenAPI spec
api2mcp generate --spec openapi.yaml --output ./server

# Run the server
api2mcp serve ./server

LangGraph 1.0 Orchestration

from api2mcp import MCPToolRegistry, PlannerGraph
from langchain_anthropic import ChatAnthropic
from langgraph.checkpoint.sqlite import SqliteSaver

# Register MCP servers
registry = MCPToolRegistry()
await registry.connect_server("github", github_config)
await registry.connect_server("jira", jira_config)

# Create orchestrator with official checkpointer
orchestrator = PlannerGraph(
    model=ChatAnthropic(model="claude-sonnet-4-5-20250929"),
    tool_registry=registry,
    api_names=["github", "jira"],
    checkpointer=SqliteSaver.from_conn_string("workflows.db"),
    execution_mode="mixed"  # parallel for independent steps
)

# Run complex workflow
result = await orchestrator.run(
    "Sync all GitHub bugs to Jira project SUPPORT"
)

Documentation

• Getting Started
• Configuration Reference
• CLI Reference
• Orchestration Tutorial
• Contributing Guide

Development

Prerequisites

• Python 3.11+
• pip or any PEP 517-compatible build tool

Setup

# Clone and install in editable mode with dev dependencies
git clone https://github.com/manavghosh/api2mcp.git
cd api2mcp
pip install -e ".[dev]"

Optional extras

pip install -e ".[dev,graphql]"    # add GraphQL parser support
pip install -e ".[dev,postgres]"   # add PostgreSQL checkpointer
pip install -e ".[dev,docs]"       # add MkDocs documentation tooling

Running tests

pytest                        # run full test suite
pytest tests/unit/            # unit tests only
pytest -m "not e2e"           # skip end-to-end tests
pytest --no-cov               # skip coverage (faster)

Linting and type-checking

ruff check .                  # lint
ruff format .                 # format
mypy src/                     # type-check

Building the package

pip install build
python -m build               # produces dist/*.whl and dist/*.tar.gz

Building the documentation site

pip install -e ".[docs]"
mkdocs serve                  # live-reload preview at http://127.0.0.1:8000
mkdocs build --strict         # static build into site/

Project Structure

api2mcp/
├── src/api2mcp/         # Source code
│   ├── orchestration/   # LangGraph integration
│   │   ├── adapters/    # MCP-to-LangChain adapters
│   │   ├── graphs/      # Workflow patterns
│   │   └── state/       # State management
│   └── ...
├── tests/               # Test suite
├── docs/                # Documentation source (MkDocs)
├── examples/            # Usage examples
└── demo/                # Runnable demos

Acknowledgements

API2MCP was built with the assistance of Claude (Anthropic). The product vision, architecture decisions, specifications, and every design trade-off were directed by the project author. Claude served as the implementation tool — the same way a framework or a compiler is a tool.

Key open source projects that power API2MCP:

Contributing

Contributions are welcome! Please read CONTRIBUTING.md and our Code of Conduct before submitting a pull request.

License

MIT License - see LICENSE for details.