dspy-mcp-tool-integration
This skill integrates Model Context Protocol (MCP) servers with DSPy agents by converting MCP tools into DSPy-compatible tools for use in ReAct agents. Use it when connecting remote or local MCP servers to DSPy, enabling agents to call external tools via streamable HTTP or stdio MCP transports, requiring async patterns and proper session lifecycle management.
git clone --depth 1 https://github.com/OmidZamani/dspy-skills /tmp/dspy-mcp-tool-integration && cp -r /tmp/dspy-mcp-tool-integration/skills/dspy-mcp-tool-integration ~/.claude/skills/dspy-mcp-tool-integrationSKILL.md
# DSPy MCP Tool Integration
## Goal
Connect an MCP server with the MCP Python client, convert its tools to `dspy.Tool`, and use them in an async DSPy agent.
## Install
```bash
pip install -U "dspy[mcp]>=3.2.1,<3.3"
```
DSPy converts tools but does not manage MCP connections. Keep the `ClientSession` alive for as long as the DSPy tools are in use.
## Streamable HTTP Server
```python
import asyncio
import dspy
from mcp import ClientSession
from mcp.client.streamable_http import streamablehttp_client
async def main():
async with streamablehttp_client("http://localhost:8000/mcp") as (read, write):
async with ClientSession(read, write) as session:
await session.initialize()
response = await session.list_tools()
tools = [dspy.Tool.from_mcp_tool(session, tool) for tool in response.tools]
agent = dspy.ReAct("task -> result", tools=tools, max_iters=5)
output = await agent.acall(task="Check the weather in Tokyo")
print(output.result)
asyncio.run(main())
```
## Local Stdio Server
```python
import asyncio
import dspy
from mcp import ClientSession, StdioServerParameters
from mcp.client.stdio import stdio_client
async def main():
params = StdioServerParameters(
command="python3",
args=["path/to/server.py"],
env=None,
)
async with stdio_client(params) as (read, write):
async with ClientSession(read, write) as session:
await session.initialize()
response = await session.list_tools()
tools = [dspy.Tool.from_mcp_tool(session, tool) for tool in response.tools]
agent = dspy.ReAct("question -> answer", tools=tools, max_iters=5)
print((await agent.acall(question="What is 25 + 17?")).answer)
asyncio.run(main())
```
## Best Practices
1. Use `acall()` because MCP tools are asynchronous.
2. Initialize the session before listing tools.
3. Keep tool descriptions precise at the MCP server boundary.
4. Apply authentication and authorization before exposing sensitive tools.
5. Set a modest `max_iters` and trace tool use in production.
## Related Skills
- Build agents: [dspy-react-agent-builder](../dspy-react-agent-builder/SKILL.md)
- Configure native function calling: [dspy-adapters-multimodal](../dspy-adapters-multimodal/SKILL.md)
- Add async runtime patterns: [dspy-production-deployment](../dspy-production-deployment/SKILL.md)
## Official Documentation
- **DSPy MCP guide**: https://dspy.ai/learn/programming/mcp/
- **DSPy MCP tutorial**: https://dspy.ai/tutorials/mcp/
- **MCP Python SDK**: https://github.com/modelcontextprotocol/python-sdkUse this skill when you need to QA audit and fix a plugin skill file. Provides a methodology for verifying skill content against official documentation, fixing issues in-place, and producing verification reports.
Use for DSPy adapter selection, JSONAdapter, XMLAdapter, ChatAdapter, native function calling, structured outputs, and multimodal inputs like dspy.Image or dspy.Audio.
Use for composing DSPy modules with Ensemble, MultiChainComparison, ensemble voting, sequential pipelines, and multi-program workflows.
Use for BetterTogether, prompt plus weight optimization, fine-tuning sequences, and strategy chains like p -> w -> p.
Use for BootstrapFewShot, bootstrapped demonstrations, teacher-model demos, and low-data DSPy prompt optimization.
Use for creating custom DSPy modules, extending dspy.Module, reusable components, stateful modules, serialization, and module testing.
Use for debugging DSPy programs, inspect_history, tracing LLM calls, custom callbacks, observability, monitoring, and cost tracking.
Use for DSPy retrieval with dspy.Embedder, dspy.Embeddings, FAISS indexes, semantic search, and local or hosted embedding models.