Building a Production-Ready MCP Server in Python

Develop a production-grade MCP server in Python with JWT auth, scope-based governance, rate limits, and OTEL tracing for both STDIO and HTTP modes.

Nabin Debnath

Dec. 01, 25 · Tutorial

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The Model Context Protocol (MCP) is rapidly emerging as a fundamental framework for secure AI integration. It effectively links large language models (LLMs) with essential corporate assets, such as APIs, databases, and services. However, moving from concept to production requires addressing several key real-world demands:

Governance: Defining clear rules regarding who is authorized to access specific tools
Security: Implementing robust practices for managing and protecting tokens and secrets
Resilience: Ensuring system stability and performance during high-demand periods or in the face of malicious attacks
Observability: Establishing the capability to effectively diagnose and troubleshoot failures across various tools and user environments

In this article, we'll focus on these points and upgrade a simple MCP server into a production-grade, robust system. We'll build:

An MCP server (stdio) for Claude Desktop and MCP Inspector
A reusable governance layer (scopes + rate limits)
OpenTelemetry tracing
An HTTP test gateway for verifying role-based access control (RBAC) and quotas using cURL
A complete runtime that you can deploy or expand upon for your own tools

Architecture Overview

The system architecture consists of several key components, each with a specific role:

MCP Server – Manages the registration and execution of tools and resources
FastAPI Gateway – An optional external entry point for remote clients, providing JSON Web Token (JWT) verification and rate-limit enforcement
Governance Decorators – Applies and enforces essential controls such as per-tool scopes, quotas, and audit context
Observability Layer – Utilizes OpenTelemetry to trace every call, with output directed to standard output (stdout) or the OpenTelemetry Protocol (OTLP)
Transport Mode – Defines the communication protocol, supporting standard input and output (stdio) for the Claude Desktop application or HTTP for remote clients

Environment Setup

To set up the environment, run the following command in your shell:

    Shell
   
   pip3 install mcp fastapi "uvicorn[standard]" pyjwt opentelemetry-sdk opentelemetry-api

Full Implementation in a Single File

Below is the complete implementation that you can run immediately. It includes:

FastMCP server (stdio)
JWT authentication (HTTP gateway)
Scope-based RBAC
Per-tenant rate limiting
OpenTelemetry tracing
Shared TOOLS registry

    Python
   
 

   """
mcp_demo.py

Production-leaning MCP server 

- FastMCP-based MCP server (stdio) for Claude Desktop / MCP Inspector
- JWT authentication + scope-based RBAC for HTTP gateway
- Simple per-tenant+tool rate limiter
- OpenTelemetry tracing to console

Install deps:
    pip install mcp fastapi "uvicorn[standard]" pyjwt \
                opentelemetry-sdk opentelemetry-api
"""

import time
from functools import wraps
from typing import Any, Callable, Dict, Optional

import jwt
from fastapi import Depends, FastAPI, Header, HTTPException
from opentelemetry import trace
from opentelemetry.sdk.resources import Resource
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.trace.export import ConsoleSpanExporter, SimpleSpanProcessor
import uvicorn

from mcp.server.fastmcp import FastMCP

# ------------------------------------------------------------------------------
# Observability (OpenTelemetry → console)
# ------------------------------------------------------------------------------

def setup_tracing(use_console: bool):
    provider = TracerProvider(
        resource=Resource.create({"service.name": "mcp-python-server"})
    )
    if use_console:
        provider.add_span_processor(SimpleSpanProcessor(ConsoleSpanExporter()))
    trace.set_tracer_provider(provider)
    return trace.get_tracer("mcp-python-server")


# ------------------------------------------------------------------------------
# Governance: scopes + rate-limit
# ------------------------------------------------------------------------------

_BUCKETS: dict[tuple[str, str], dict[str, float]] = {}


def rate_limit(calls: int, per_seconds: float):
    """Simple token-bucket rate limiter per (tenant, tool)."""

    def deco(fn: Callable):
        @wraps(fn)
        def wrapper(
            *args,
            tenant_id: str = "public",
            tool_name: str = "",
            **kwargs,
        ):
            key = (tenant_id, tool_name or fn.__name__)
            bucket = _BUCKETS.setdefault(
                key, {"tokens": calls, "ts": time.time()}
            )
            now = time.time()

            # Refill tokens
            bucket["tokens"] = min(
                calls,
                bucket["tokens"] + (now - bucket["ts"]) * (calls / per_seconds),
            )
            bucket["ts"] = now

            if bucket["tokens"] < 1:
                raise RuntimeError(f"Rate limit exceeded for {key}")

            bucket["tokens"] -= 1

            with tracer.start_as_current_span(
                f"rate_limit.{tool_name or fn.__name__}"
            ):
                return fn(*args, tenant_id=tenant_id, **kwargs)

        return wrapper

    return deco


def require_scopes(*needed: str):
    """
    Scope-based RBAC decorator.

    - If granted_scopes is None (stdio mode / trusted local host),
      we allow everything (no RBAC).
    - If granted_scopes is provided (HTTP gateway w/ JWT), we enforce it.
    """

    def deco(fn: Callable):
        @wraps(fn)
        def wrapper(
            *args,
            granted_scopes: Optional[list[str]] = None,
            **kwargs,
        ):
            if granted_scopes is None:
                # Local/stdio mode: skip RBAC
                return fn(*args, **kwargs)

            granted = set(granted_scopes)
            missing = [s for s in needed if s not in granted]
            if missing:
                raise PermissionError(f"Missing scopes: {missing}")
            return fn(*args, granted_scopes=granted_scopes, **kwargs)

        return wrapper

    return deco


# ------------------------------------------------------------------------------
# Auth: JWT helpers (used by HTTP gateway)
# ------------------------------------------------------------------------------

JWT_SECRET = "replace-me-in-prod"
JWT_ALG = "HS256"


def decode_jwt(token: str) -> Dict[str, Any]:
    return jwt.decode(token, JWT_SECRET, algorithms=[JWT_ALG])


def mint_demo_jwt(
    sub: str = "user-123",
    tenant: str = "acme",
    scopes: Optional[list[str]] = None,
) -> str:
    scopes = scopes or ["customer:read", "orders:search"]
    payload = {
        "sub": sub,
        "tenant": tenant,
        "scopes": scopes,
        "exp": int(time.time()) + 3600,
    }
    return jwt.encode(payload, JWT_SECRET, algorithm=JWT_ALG)


# ------------------------------------------------------------------------------
# MCP server (FastMCP) – tools & resources
# ------------------------------------------------------------------------------

mcp = FastMCP("Python MCP Demo")

# Simple registry for HTTP gateway → names → functions
TOOLS: Dict[str, Callable[..., Any]] = {}


@mcp.tool()
@require_scopes("customer:read")
@rate_limit(calls=5, per_seconds=10)
def get_customer(
    customer_id: str,
    tenant_id: str = "public",
    granted_scopes: Optional[list[str]] = None,
) -> dict:
    """Return a sanitized customer profile (read-only)."""
    with tracer.start_as_current_span("tool.get_customer") as span:
        span.set_attribute("tenant.id", tenant_id)
        span.set_attribute("customer.id", customer_id)
        return {"id": customer_id, "name": "Jane Doe", "tier": "gold"}


TOOLS["get_customer"] = get_customer  # register for HTTP


@mcp.tool()
@require_scopes("orders:search")
@rate_limit(calls=10, per_seconds=10)
def find_orders(
    query: str,
    tenant_id: str = "public",
    granted_scopes: Optional[list[str]] = None,
) -> list[dict]:
    """Search orders via a safe path (no raw SQL from the model)."""
    with tracer.start_as_current_span("tool.find_orders") as span:
        span.set_attribute("tenant.id", tenant_id)
        span.set_attribute("query", query[:64])
        return [{"order_id": "o-123", "status": "shipped"}]


TOOLS["find_orders"] = find_orders  # register for HTTP


@mcp.resource("customers://{customer_id}")
def customer_resource(customer_id: str) -> str:
    """Simple resource example that could be expanded to DB/HTTP fetch."""
    return (
        f'{{"doc": "Customer {customer_id} resource placeholder"}}'
    )


# ------------------------------------------------------------------------------
# HTTP gateway (for testing JWT + quotas; separate from MCP transport)
# ------------------------------------------------------------------------------

app = FastAPI(title="MCP Demo Gateway")


def auth(
    Authorization: Optional[str] = Header(default=None),
) -> Dict[str, Any]:
    if not Authorization or not Authorization.startswith("Bearer "):
        raise HTTPException(status_code=401, detail="Missing bearer token")
    token = Authorization.split()[1]
    try:
        return decode_jwt(token)
    except Exception as exc:  # noqa: BLE001
        raise HTTPException(status_code=401, detail=f"Invalid token: {exc}") from exc


@app.get("/mint-demo-jwt")
def mint_token() -> Dict[str, str]:
    """Convenience helper: get a working JWT for local curl tests."""
    return {"token": mint_demo_jwt()}


@app.post("/mcp/tool/{name}")
def call_tool_http(
    name: str,
    payload: dict,
    ctx: Dict[str, Any] = Depends(auth),
):
    """
    HTTP entry point that reuses the same Python functions as MCP tools.

    NOTE:
    - This is NOT MCP-over-HTTP; it's a convenience gateway so you can
      see JWT scopes + rate limiting in action with curl/Postman.
    """
    fn = TOOLS.get(name)
    if fn is None:
        raise HTTPException(status_code=404, detail="Unknown tool")

    tenant_id = ctx.get("tenant", "public")
    scopes = ctx.get("scopes", [])

    # Inject governance context
    payload.setdefault("tenant_id", tenant_id)
    payload.setdefault("granted_scopes", scopes)

    try:
        result = fn(**payload)
        return {"ok": True, "result": result}
    except PermissionError as exc:  # from require_scopes
        raise HTTPException(status_code=403, detail=str(exc)) from exc
    except RuntimeError as exc:  # from rate_limit
        raise HTTPException(status_code=429, detail=str(exc)) from exc
    except TypeError as exc:
        raise HTTPException(status_code=400, detail=f"Bad args: {exc}") from exc


def run_http(port: int = 8080) -> None:
    uvicorn.run(app, host="0.0.0.0", port=port)


# ------------------------------------------------------------------------------
# Entry points: stdio (MCP) & HTTP (testing)
# ------------------------------------------------------------------------------


def run_stdio():
    """
    Run FastMCP over stdio.

    This is what Claude Desktop / MCP Inspector will use.
    """
    # FastMCP handles stdio transport internally
    mcp.run(transport="stdio")



if __name__ == "__main__":
    import argparse

    parser = argparse.ArgumentParser()
    parser.add_argument(
        "--mode",
        choices=["stdio", "http"],
        default="http",
        help="Run as stdio MCP server or HTTP gateway",
    )
    parser.add_argument("--port", type=int, default=8080)
    args = parser.parse_args()

if args.mode == "stdio":
    tracer = setup_tracing(use_console=False)
    run_stdio()
else:
    tracer = setup_tracing(use_console=True)
    run_http(args.port)

  

Running the Application in HTTP Mode (JWT, RBAC, Rate Limit Testing)

To start, run the following command:

    Shell
   
   python mcp_demo.py --mode http

Happy Path

Use the following command to obtain a JWT Token:

    Shell
   
   curl -s http://localhost:8080/mint-demo-jwt | jq -r .token > token.txt
TKN=$(cat token.txt)

Now, you can make an authorized call using the token:

    Shell
   
   curl -s -X POST http://localhost:8080/mcp/tool/get_customer \
  -H "Authorization: Bearer $TKN" \
  -H "Content-Type: application/json" \
  -d '{"customer_id":"c-42"}'

You should receive the following JSON response:

    JSON
   
   {"ok":true,"result":{"id":"c-42","name":"Jane Doe","tier":"gold"}}

In the server console, you will also see OpenTelemetry printing spans:

RBAC Denial (Missing Scope)

To test the RBAC denial, create a token without customer:read and try again:

    Shell
   
 

   # Token with only orders:search
python - <<'PY'
import jwt, time
print(jwt.encode(
  {"sub":"user-999","tenant":"acme","scopes":["orders:search"],"exp":int(time.time())+3600},
  "replace-me-in-prod", algorithm="HS256"))
PY
# copy to $WEAK
WEAK=<generated token above>

curl -i -X POST "http://localhost:8080/mcp/tool/get_customer" \
  -H "Authorization: Bearer $WEAK" \
  -H "Content-Type: application/json" \
  -d '{"customer_id":"c-1"}'

  

You should receive the following JSON response:

    JSON
   
   {"detail":"Missing scopes: ['customer:read']"}

Rate-Limit in Action

To test the rate limit, call get_customer more than 5 times within ~10 seconds:

    Shell
   
   for i in $(seq 1 7); do
  curl -s -o /dev/null -w "%{http_code}\n" -X POST "http://localhost:8080/mcp/tool/get_customer" \
    -H "Authorization: Bearer $TKN" -H "Content-Type: application/json" \
    -d '{"customer_id":"c-rl"}'
done

Expected Output:

You should see some responses with 200, followed by 429. This confirms that the quota enforcement is working per (tenant, tool).

Running the Application in STDIO Mode (Claude Desktop)

To run the server in stdio mode, execute:

    Shell
   
   python mcp_demo.py --mode stdio

Configure Claude Desktop to Launch the Same Command:

Install Claude Desktop
Open the claude_desktop_config.json file under Settings -> Developer -> Edit Config
Replace it with the following JSON:

    JSON
   
 

   {
  "mcpServers": {
    "my-python-mcp": {
      "command": "python",
      "args": ["/ABSOLUTE/PATH/mcp_demo.py", "--mode=stdio"],
    }
  }
}
  

Save the file and restart Claude Desktop

Test Inside Claude

Open a chat and request it to use a tool, for example: "Call the get_customer MCP tool with id c-42."

The Claude Desktop should now be able to communicate with the MCP tool.

Running the Application in STDIO Mode (MCP Inspector)

If you have uv installed, run uv run mcp dev mcp_demo.py. Alternatively, you can run the MCP inspector with Python (without uv).

    Shell
   
   npx -y @modelcontextprotocol/inspector python mcp_demo.py --mode stdio

What Makes This "Production-Ready"

Security

JWT authentication
Scope-based RBAC for each tool
Least-privilege design principles
No raw SQL or direct OS access from tools
Utilizes secrets from environment (transition to Vault/KMS in production)

Governance

Per-tenant, per-tool rate limiting
Centralized decorators for policy enforcement
Deterministic error codes (403 for Forbidden, 429 for Too Many Requests)

Observability

OpenTelemetry spans for:
- Tool execution
- Tenant ID
- Latency
- Errors
- Rate-limit events

Reliability

Structured failure handling
Reusable shared tool logic (stdio + HTTP)
Compatibility with Docker, Kubernetes, AWS Lambda

Developer Experience

Stdio mode for Claude/Desktop workflows
HTTP gateway for integration tests using Postman or cURL
Fully testable Continuous Integration (CI) suite

Key Takeaways

MCP becomes powerful when combined with production-grade abstractions such as authentication, RBAC, and observability.
FastMCP simplifies the exposure of Python tools via stdio for Claude Desktop.
A custom TOOLS registry enables testing controls through HTTP.
OpenTelemetry provides distributed tracing across tool interactions.
Rate limiting and RBAC transform tools into governable and auditable enterprise APIs.

JSON JWT (JSON Web Token) Production (computer science) Python (language) security

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