Serve an agent over MCP

Every other page in this section points an agent at an MCP server. This one makes an agent into one. Once it is served, any MCP client can call it as a tool: another Swarms agent, Claude Desktop, Cursor, or a script in another language.


Class	`MCPDeployer`
Transport	streamable HTTP, `http://127.0.0.1:8000/mcp`
Auth	one static API key
Model used here	`claude-sonnet-5`

Prerequisites

pip install -U swarms "mcp>=2.0.0"
export ANTHROPIC_API_KEY="sk-ant-..."

MCPDeployer needs mcp 2.0.0 or newer.

Build it

Write the server

The agent you want to share is an ordinary Agent. agent_description becomes the tool description the calling model reads, so write it for a reader with no other context.

server.py

from swarms import Agent, MCPDeployer

analyst = Agent(
    agent_name="Market-Analyst",
    agent_description="Answers questions about markets and companies in three sentences or fewer.",
    system_prompt="You are a concise market analyst. Answer in three sentences or fewer.",
    model_name="claude-sonnet-5",
    max_loops=1,
    print_on=False,
)

if __name__ == "__main__":
    MCPDeployer(
        analyst,
        api_keys=["sk-local-dev"],
        port=8000,
    ).run()

The tool is named after the agent: Market-Analyst becomes market_analyst.

Run it

python server.py

It prints a banner with the URL and keeps serving. Leave it running.

Check it from a second terminal

/health is public:

curl http://127.0.0.1:8000/health

{"status":"ok","name":"market_analyst","tool":"market_analyst","tools":["market_analyst"],"transport":"streamable-http"}

The MCP endpoint is not. A request with no key, or the wrong one, gets 401:

curl -s -o /dev/null -w "%{http_code}\n" -X POST http://127.0.0.1:8000/mcp
curl -s -o /dev/null -w "%{http_code}\n" -X POST -H "x-api-key: wrong" http://127.0.0.1:8000/mcp

401
401

Call it from another agent

The client is an ordinary agent too. MCPConnection carries the URL and the key.

client.py

from swarms import Agent
from swarms.schemas.mcp_schemas import MCPConnection

manager = Agent(
    agent_name="Portfolio-Manager",
    system_prompt=(
        "You manage a portfolio. Use the market_analyst tool for any "
        "market question, then summarise its answer in one sentence."
    ),
    model_name="claude-sonnet-5",
    mcp_url=MCPConnection(
        url="http://127.0.0.1:8000/mcp",
        api_key="sk-local-dev",
    ),
    max_loops=2,
    print_on=False,
    output_type="final",
)

print(manager.run("What is the main risk to semiconductor stocks right now?"))

python client.py

The portfolio manager discovers market_analyst, calls it with the question as task, and summarises what the analyst returned. The server terminal logs each request.

What just happened

MCPDeployer wrapped analyst as one MCP tool with the schema task: str, img: str | None.
Every request to /mcp went through the auth layer first. The key can arrive as x-api-key or as Authorization: Bearer, which is what MCPConnection sends.
The tool call ran analyst.run(task) on a worker thread and returned its answer as the tool result.

Variations

Keys from the environment instead of the code. api_key_env reads a comma-separated list, so you can rotate keys without a code change:

MCPDeployer(analyst, api_key_env="ANALYST_MCP_KEYS", port=8000).run()

Run the server inside your own script. start() and stop(), or a with block, run it on a background thread:

with MCPDeployer(analyst, api_keys=["sk-local-dev"], port=8000) as server:
    print(server.url)

Reachable from other machines. Bind to all interfaces and put TLS in front of it:

MCPDeployer(analyst, api_keys=["sk-prod-..."], host="0.0.0.0", port=8000).run()

Launched by an MCP host. Claude Desktop and similar hosts start servers as subprocesses over stdio. There are no HTTP headers on stdio, so the host itself is the security boundary:

MCPDeployer(analyst, transport="stdio", allow_anonymous=True).run()

Serve a team from one server

Several agents, a workflow, and a function, each its own tool.

MCPDeployer reference

Every parameter, auth mode, and method.

Index

Basic Examples

Model Providers

Single Agent

Multi-Agent Examples

Auto Agent Builder

Scheduled Agents

Applications

Research

Technical Analysis

Use Cases

Finance

Voice Agents

Integrations

MCP Tool Integrations

Deployment

CLI

Serve an agent over MCP

Prerequisites

Build it

What just happened

Variations

Next

Serve a team from one server

MCPDeployer reference

​Prerequisites

​Build it

​What just happened

​Variations

​Next

Serve a team from one server

MCPDeployer reference

Prerequisites

Build it

What just happened

Variations

Next