pontifex-mcp 0.3.0

The security, access-control, and governance layer for MCP servers.

pontifex-mcp

Enterprise-grade capabilities for MCP servers, built on the official MCP Python SDK.

pontifex-mcp lets you build MCP servers that connect AI agents to real systems without giving up control over who can call what. You write the tools; it handles authentication, per-caller scopes, rate limits, and a full audit trail.

Key features

• Secure by default — OAuth 2.1 JWTs and sk_… API keys; every tool call is authenticated. Any OIDC provider (Auth0, Entra, Clerk, Keycloak).
• Least-privilege scopes — domain:resource:action, checked before every call. Callers can't widen their own access.
• Auditable — every call recorded: who, what, when, data source, cache hit, latency.
• Standards-based — RFC 9728 discovery + WWW-Authenticate; MCP clients bootstrap auth on their own.
• Resilient — per-caller rate limiting, adapter failover, circuit breaking.
• Observable — Logfire / OpenTelemetry tracing and metrics wired in.
• Built on the MCP SDK — keep its tools, protocol, and transports; add the controls a production server needs.

Security is deliberate: asymmetric-only JWT validation, generic auth errors, and no token claim can escalate a caller — all verifiable in the source.

Status: 0.x, building in public. The security model is solid; the public API (everything exported from pontifex_mcp) is still settling — expect occasional breaking changes before 1.0.

Install

pip install pontifex-mcp     # or: uv add pontifex-mcp

Requires Python 3.12+, Postgres, and Redis.

Build your own domain

A domain is: a settings class, one or more data adapters, and tools wrapped with tool_runtime. Everything below comes from the top-level package.

from typing import Any

from mcp.server.fastmcp import Context, FastMCP
from pontifex_mcp import (
    AuditWriter,
    CoreSettings,
    create_mcp_http_app,
    tool_runtime,
)


class OrdersSettings(CoreSettings):
    orders_api_base: str = "https://orders.internal.example.com"


def register_tools(mcp: FastMCP, audit: AuditWriter) -> None:
    @mcp.tool(name="orders_get_status", description="Look up the status of an order.")
    @tool_runtime(
        domain="orders",
        tool_name="orders_get_status",
        resource="order",        # scope checked: orders:order:read
        action="read",
        audit=audit,
    )
    async def get_order_status(order_id: str, ctx: Context | None = None) -> dict[str, Any]:
        # ... fetch from your internal system (ideally through a DataAdapter) ...
        return {"source": "orders-api", "cache_hit": False, "order_id": order_id, "status": "shipped"}


async def health() -> dict[str, Any]:
    return {"status": "ok"}


settings = OrdersSettings()
app = create_mcp_http_app("orders", settings, register_tools, health)
# `uv run uvicorn your_module:app` → MCP endpoint at /mcp, health at /health/ready

Auth, scope checks, rate limiting, the audit row, and the structured error envelope are all applied by tool_runtime and the server's middleware — your handler just returns data.

Configuration

Infrastructure settings read from bare, unprefixed env vars:

DATABASE_URL, REDIS_URL          # required (the app fails fast if unset)
AUTH_JWKS_URL, AUTH_ISSUER, AUTH_AUDIENCE, AUTH_SCOPES_CLAIM   # enable the OAuth/JWT path
PUBLIC_BASE_URL                  # canonical URL advertised in OAuth discovery

Domain-specific settings on your subclass read with your domain's env_prefix.

Who it's for

Reach for pontifex-mcp when you're exposing internal or proprietary systems — an orders API, a customer database, an analytics warehouse — to AI agents (Claude Desktop, your own agents, anything that speaks MCP), and unauthenticated tool access isn't an option.

If you're shipping a single public tool over non-sensitive data, the MCP SDK on its own is simpler. Come here when access control and an audit trail start to matter.

License

MIT © Chris Dare. Part of Argonauts.