qiskit-docs-mcp-server 0.2.0

MCP server for Qiskit documentation retrieval and search

qiskit-docs-mcp-server

MCP server for querying and retrieving Qiskit documentation, guides, and API references.

Overview

The Qiskit Documentation MCP Server provides AI assistants and agents with seamless access to the complete Qiskit documentation ecosystem. It enables intelligent retrieval of SDK module documentation, implementation guides, and best practices through a standardized Model Context Protocol interface.

Key Features

• 📚 Complete Documentation Access: Query all Qiskit SDK modules, addon packages, API references, guides, and tutorials
• 🔄 Dynamic Content Discovery: Automatically discovers available documentation from the live sitemap — no manual updates needed when new content is published
• 📖 Implementation Guides: Access best practices for optimization, error mitigation, dynamic circuits, and more
• 🔍 Smart Search: Search across the entire Qiskit documentation with fuzzy matching
• 🎯 No Authentication Required: Public documentation access without API tokens
• 📝 Markdown Output: Clean, formatted documentation ready for AI consumption
• ⚡ Fast Retrieval: Efficient HTTP-based documentation fetching with TTL caching and configurable timeouts

Components

Tools

The server implements three tools for documentation access:

Tool	Description	Parameters
search_docs_tool	Search across the entire Qiskit documentation for relevant content	query: Search query string scope: Search scope filter — all (default), documentation, api, learning, tutorials
get_page_tool	Fetch any Qiskit documentation page and return as markdown	url: Full URL or relative path (e.g., guides/transpile, api/qiskit/circuit) max_length: Max characters to return (default: 20000, 0 for unlimited) offset: Character offset for pagination (default: 0)
lookup_error_code_tool	Look up a Qiskit/IBM Quantum error code	code: 4-digit error code (e.g., 1002, 7001, 8004)

Resources

The server provides six resources for listing available documentation. Content lists for modules, addons, guides, tutorials, and API packages are dynamically discovered from the documentation sitemap and cached, with hardcoded fallback values used when the sitemap is unreachable.

Resource URI	Description
qiskit-docs://modules	List of all Qiskit SDK modules with URL paths
qiskit-docs://addons	List of Qiskit addon packages with URL paths
qiskit-docs://guides	List of implementation guides and best practices
qiskit-docs://tutorials	List of Qiskit tutorials with URL paths
qiskit-docs://api-packages	List of API packages (runtime, transpiler, REST APIs, etc.)
qiskit-docs://error-codes	List of Qiskit error code categories

Resource Templates

Resource URI	Description
qiskit-docs://modules/{module_name}	Documentation for a specific SDK module
qiskit-docs://guides/{guide_name}	A specific implementation guide
qiskit-docs://addons/{addon_name}	Documentation for a specific addon package

Prerequisites

• Python 3.10 or higher
• uv package manager (recommended)
• Internet connection to access IBM Quantum Documentation

Installation

Install from PyPI

The easiest way to install is via pip:

pip install qiskit-docs-mcp-server

Or using uvx (recommended):

uvx qiskit-docs-mcp-server

Install from Source

This project uses uv for virtual environments and dependencies management. If you don't have uv installed, check out the instructions in https://docs.astral.sh/uv/getting-started/installation/

Setting up the Project with uv

1. Clone the repository:

   git clone https://github.com/Qiskit/mcp-servers.git
   cd mcp-servers/qiskit-docs-mcp-server
   

2. Initialize or sync the project:

   # This will create a virtual environment and install dependencies
   uv sync
   

Configuration

Environment Variables

The server can be configured using environment variables:

Variable	Description	Default
QISKIT_DOCS_BASE	Base URL for Qiskit documentation	https://quantum.cloud.ibm.com/docs/
QISKIT_HTTP_TIMEOUT	HTTP request timeout in seconds	10.0
QISKIT_DOCS_CACHE_TTL	Page cache TTL in seconds	3600.0
QISKIT_SEARCH_CACHE_TTL	Search/JSON cache TTL in seconds	300.0
QISKIT_SEARCH_BASE_URL	Search API base URL	https://quantum.cloud.ibm.com/

Optional Configuration

Create a .env file in the project directory:

# Optional: Customize documentation URLs
QISKIT_DOCS_BASE=https://quantum.cloud.ibm.com/docs/
QISKIT_HTTP_TIMEOUT=15.0
QISKIT_DOCS_CACHE_TTL=3600.0
QISKIT_SEARCH_CACHE_TTL=300.0

Quick Start

Running the Server

uv run qiskit-docs-mcp-server

The server will start and listen for MCP connections.

Using with MCP Clients

Claude Desktop Configuration

Add to your Claude Desktop configuration file:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json Windows: %APPDATA%\Claude\claude_desktop_config.json

{
  "mcpServers": {
    "qiskit-docs": {
      "command": "uvx",
      "args": ["qiskit-docs-mcp-server"]
    }
  }
}

Cline Configuration

Add to your Cline MCP settings:

{
  "mcpServers": {
    "qiskit-docs": {
      "command": "uvx",
      "args": ["qiskit-docs-mcp-server"]
    }
  }
}

LangChain Integration Example

Note: To run LangChain examples you will need to install the dependencies:

pip install langchain-mcp-adapters langchain-openai langgraph

import asyncio

from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent

async def main():
    # Configure MCP client
    async with MultiServerMCPClient(
        {
            "qiskit-docs": {
                "command": "qiskit-docs-mcp-server",
                "args": [],
                "transport": "stdio",
            }
        }
    ) as client:
        # Create agent with LLM and MCP tools
        agent = create_react_agent(
            ChatOpenAI(model="gpt-4o"),
            client.get_tools(),
        )

        # Query documentation
        response = await agent.ainvoke(
            {"messages": [("user", "How do I create a quantum circuit in Qiskit?")]}
        )
        print(response["messages"][-1].content)

asyncio.run(main())

Usage Examples

Search Documentation

# Search for transpiler information
result = await search_docs_tool("transpiler optimization")
print(f"Found {result['total_results']} results")
for item in result["results"]:
    print(f"- {item['title']}: {item['url']}")

Fetch a Documentation Page

# Fetch circuit module API reference
result = await get_page_tool("api/qiskit/circuit")
print(result["documentation"])

# Fetch with pagination for large pages
result = await get_page_tool("api/qiskit/circuit", max_length=5000)
if result["has_more"]:
    next_page = await get_page_tool("api/qiskit/circuit", offset=result["next_offset"])

Look Up an Error Code

# Look up error code 1002
result = await lookup_error_code_tool("1002")
print(result["details"])

Available Documentation

SDK Modules

Module	Description
circuit	Quantum circuit construction and manipulation
quantum_info	Quantum information theory utilities
transpiler	Circuit transpilation and optimization
synthesis	Circuit synthesis algorithms
dagcircuit	DAG representation of quantum circuits
passmanager	Transpiler pass manager framework
converters	Circuit format converters
compiler	High-level compilation routines
primitives	Sampler and Estimator primitives
providers	Backend providers and job management
result	Job result handling and analysis
visualization	Circuit and result visualization
qasm2	OpenQASM 2.0 support
qasm3	OpenQASM 3.0 support
qpy	Qiskit Python serialization format
utils	General utility functions
exceptions	Qiskit exception classes

Implementation Guides

Guide	Description
quick-start	Get started with Qiskit
construct-circuits	Build and manipulate quantum circuits
transpile	Transpile circuits for target backends
transpiler-stages	Understand transpiler pipeline stages
configure-error-mitigation	Configure error mitigation for primitives
configure-error-suppression	Configure error suppression techniques
primitives	Use Sampler and Estimator primitives
execution-modes	Job, session, and batch execution modes
dynamic-circuits	Mid-circuit measurements and classical control
functions	Overview of Qiskit Functions

See the qiskit-docs://guides resource for the complete list of 30+ available guides.

Features

Pagination Support

Large documentation pages are automatically paginated. Use max_length and offset to control content retrieval:

# Fetch first 5000 characters
result = await get_page_tool("api/qiskit/circuit", max_length=5000)
# result["has_more"] == True, result["next_offset"] == 5000

# Fetch unlimited content
result = await get_page_tool("api/qiskit/circuit", max_length=0)

Metadata Inclusion

All responses include rich metadata:

{
    "status": "success",
    "url": "https://quantum.cloud.ibm.com/docs/api/qiskit/circuit",
    "documentation": "...",
    "has_more": False,
    "total_length": 15420,
    "metadata": {
        "url": "https://quantum.cloud.ibm.com/docs/api/qiskit/circuit",
        "timestamp": "2026-03-03T03:00:00Z",
        "content_type": "markdown",
        "content_length": 15420
    }
}

Dynamic Sitemap Discovery

Resource lists (modules, addons, guides, tutorials, API packages) are automatically discovered from the live documentation sitemap at startup. This means the server adapts to new content without code changes. If the sitemap is unreachable, the server falls back to hardcoded values in constants.py.

To update the hardcoded fallback values from the live sitemap:

cd qiskit-docs-mcp-server
uv run python scripts/update_fallback_constants.py

This prints updated constant lists that can be copied into constants.py.

HTML to Markdown Conversion

Documentation is automatically converted from HTML to clean Markdown format, optimized for AI consumption and human readability.

Development

Project Structure

src/qiskit_docs_mcp_server/
├── server.py           # MCP server definition (tools, resources, prompts)
├── data_fetcher.py     # Business logic for fetching and processing documentation
├── http.py             # HTTP infrastructure: client management, caching, retries
├── sitemap.py          # Dynamic sitemap discovery and page classification
├── html_processing.py  # HTML content extraction and markdown conversion
└── constants.py        # Configuration constants and hardcoded fallback values

scripts/
└── update_fallback_constants.py  # Regenerate fallback values from live sitemap

Running Tests

# Run all tests
./run_tests.sh

# Or use pytest directly
uv run pytest tests/ -v

# Run with coverage
uv run pytest tests/ --cov=src --cov-report=html

Code Quality

# Format code
uv run ruff format src/ tests/

# Lint code
uv run ruff check src/ tests/

# Type check
uv run mypy src/

Examples

See the examples/ directory for complete working examples:

• langchain_agent.py - LangChain agent with multiple LLM providers
• langchain_agent.ipynb - Interactive Jupyter notebook tutorial
• README.md - Detailed examples documentation

Troubleshooting

Connection Issues

Problem: "Failed to fetch documentation" Solution: Check your internet connection and verify access to https://quantum.cloud.ibm.com/docs/

Timeout Errors

Problem: "Request timed out" Solution: Increase the timeout value:

export QISKIT_HTTP_TIMEOUT=30.0

Page Not Found

Problem: "Failed to fetch" error from get_page_tool Solution: Use search_docs_tool to find the correct URL, or check the qiskit-docs://modules and qiskit-docs://guides resources for valid paths

Contributing

Contributions are welcome! Please see the CONTRIBUTING.md file in the repository root for guidelines.

License

This project is licensed under the Apache License 2.0 - see the LICENSE file for details.

Links

• Qiskit Documentation
• Model Context Protocol
• MCP Registry
• GitHub Repository

Support

For issues and questions:

• GitHub Issues
• Qiskit Slack