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Zaira-Shahid

Enterprise MCP Gateway

by Zaira-Shahid

Enterprise MCP Gateway

Secure AI-to-business tool infrastructure built on the Model Context Protocol.

A production-oriented MCP gateway that lets an AI agent work with CRM, order, support and automation systems — with authentication, RBAC, a policy engine, prompt-injection defences, audit logging, rate limiting, idempotency, observability, n8n integration and a remote Streamable HTTP transport.

Status: under active construction. docs/implementation-status.md records exactly which phases are complete and verified. Nothing is claimed here that has not been executed.


What MCP is, in one paragraph

The Model Context Protocol is an open protocol that lets an AI host discover and call capabilities exposed by a server: tools (actions and queries), resources (authoritative read-only context) and prompts (reusable, parameterised instructions). It standardises the wire format so any compliant host can talk to any compliant server. What it deliberately does not do is decide who is allowed to call what — that is the server's job, and that is what this project is about.

Related MCP server: AI-Assisted CRM MCP Server

What this project solves

Connecting an LLM to real business systems is not a tooling problem, it is a trust boundary problem. A naive MCP server hands an agent unmediated access to production data. This gateway inserts the layer a company actually needs:

  • the caller's identity comes from a verified bearer token, never from a tool argument;

  • every tool declares its required permission, risk level and audit class in one authoritative registry, and the server enforces it before any business code runs;

  • high-risk actions (sending customer email, triggering automations) require explicit confirmation and are idempotent;

  • customer-authored text is treated as untrusted data and is labelled as such when it reaches the model, so "ignore your instructions" in a ticket body is just a string;

  • every consequential operation lands in an append-only audit trail.

Architecture

AI Host / Agent  →  MCP Client  →  Enterprise MCP Gateway  →  Business systems

                    observability → audit → authn → authz →
                    rate limit → policy → idempotency → tool handler
                                                          ↓
                                                application services
                                                          ↓
                                     PostgreSQL · Redis · n8n · email adapter

Full detail, sequence diagrams and trust boundaries: docs/architecture.md.

Technology

Layer

Choice

Runtime

Python 3.12+ (developed on 3.14.3)

MCP

Official Python SDK mcp==2.1.1 (v2 API: MCPServer, ServerMiddleware)

Transports

stdio (local) and Streamable HTTP (remote)

Data

PostgreSQL via SQLAlchemy 2 + Alembic

Cache / limits

Redis

Automation

n8n

Auth

OIDC/JWT (JWKS), with a separated development mode

Observability

structlog + OpenTelemetry

Rationale for each choice, including what was rejected: docs/technology-decisions.md.

Documentation

Document

Contents

architecture.md

Layering, middleware pipeline, sequences, trust boundaries

technology-decisions.md

Stack choices and rejected alternatives

implementation-status.md

Per-phase status, tests run, known limitations

Security, tool catalogue, deployment, threat model and the demo script are added in their corresponding phases.

Licence

MIT — see LICENSE.

A
license - permissive license
Not graded
quality - not tested
C
maintenance

Maintenance

Maintainers
Response time
Release cycle
Releases (12mo)
Commit activity

Resources

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