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MCP Forge

The trusted operating layer for MCP servers. A platform where users can discover MCP servers, inspect capabilities, see trust and security signals, install them locally or remotely, test them in a sandbox, and export ready-to-use configs for Claude, OpenAI-compatible clients, editors, and custom agent runtimes.

License: MIT Discord GitHub Stars


🚀 Product Shape

Working Concept

MCP Forge is a trusted operating layer for the MCP (Model Context Protocol) ecosystem. Unlike simple awesome lists that are easy to copy, MCP Forge provides:

  • Trust infrastructure (validation, probing, scoring)
  • Runtime execution (sandbox testing, local/remote launches)
  • Compatibility tooling (client-specific config generators)
  • Security hardening (scope analysis, SSRF detection, least-privilege enforcement)
  • Ecosystem growth (maintainer incentives, federation, monetization)

Positioning Sentence

The trusted operating layer for MCP servers.


📋 Roadmap Status (15 Phases)

Phase Title Status Key Deliverables
Phase 1 Foundation COMPLETED Manifest spec, validator CLI, registry schema, dual-backend scaffold (Actix/Axum)
Phase 2 Real Utility COMPLETED Runtime probe, install generator, trust scoring, compatibility matrix
Phase 3 Differentiation COMPLETED Sandbox tester, security policy analysis, reproducible release snapshots, maintainer dashboard
Phase 4 Performance COMPLETED Benchmarking suite, latency/throughput metrics, optimization guides
Phase 5 Observability Pending Centralized logging, Prometheus/Grafana dashboards, OpenTelemetry tracing
Phase 6 Enterprise Security Pending SAML/OAuth, audit trails, policy packs, least-privilege enforcement
Phase 7 Ecosystem Growth Pending Stars/badges, maintainer bounties, curated collections, "Works with X" badges
Phase 8 Client Diversity Pending Ollama, LM Studio, LocalAI, and custom client config generators
Phase 9 Advanced MCP Features Pending Roots/sampling support in sandbox, structured output validation, progress/cancellation
Phase 10 Offline Mode Pending Air-gapped registry mirroring, offline validation, local-first mode
Phase 11 Automation Pending GitHub/GitLab CI/CD integration, automatic manifest validation, PR checks
Phase 12 Documentation Pending Interactive tutorials, API docs (Swagger/OpenAPI), video guides, CLI man pages
Phase 13 Monetization Pending Private registries, priority support, premium features (e.g., "Verified Publisher" badge)
Phase 14 Federation Pending Mirror registries, team namespaces, upstream sync, private enterprise registries
Phase 15 AI-Powered Curation Pending AI-driven package recommendations, auto-generated docs, smart search

🗺️ Phase 4: Performance

Goals

  • Benchmark MCP servers for latency, throughput, and resource usage.
  • Provide optimization guides for high-throughput deployments.
  • Integrate performance metrics into the trust score.

Deliverables

Component Description
mcp-benchmark CLI Run standardized benchmarks (e.g., 1K requests, 1MB payloads) and generate reports.
Performance Dashboard Visualize latency/throughput metrics in the maintainer dashboard.
Optimization Guides Documentation for tuning MCP servers (e.g., async I/O, connection pooling).
Trust Score Integration Adjust trust score based on performance metrics (e.g., sub-100ms latency bonus).

Architecture

MCP-Forge/
├── packages/
│   ├── benchmark/       # Benchmarking suite (Python/Go)
│   │   ├── scenarios/   # Standardized test scenarios
│   │   └── reporter.py  # Generate HTML/PDF reports
│   └── scoring/         # Trust score integration
└── apps/web/            # Performance dashboard UI

🗺️ Phase 5: Observability

Goals

  • Centralize logs, metrics, and traces for deployed MCP servers.
  • Provide dashboards for monitoring health, performance, and security.

Deliverables

Component Description
OpenTelemetry Integration Instrument MCP servers for distributed tracing.
Prometheus/Grafana Dashboards Pre-built dashboards for latency, error rates, and resource usage.
Centralized Logging Aggregate logs from multiple MCP servers into a single view.
Alerting Notify maintainers of anomalies (e.g., high latency, failed probes).

Architecture

MCP-Forge/
├── packages/
│   └── observability/   # OpenTelemetry SDK, Prometheus exporters
└── apps/
    └── web/               # Grafana dashboard templates

🗺️ Phase 6: Enterprise Security

Goals

  • Support enterprise authentication (SAML/OAuth).
  • Enforce least-privilege policies and audit trails.

Deliverables

Component Description
SAML/OAuth Integration Support enterprise identity providers (Okta, Azure AD).
Audit Trails Log all registry actions (publish, install, verify) for compliance.
Policy Packs Pre-built security policies (e.g., "No network egress", "Read-only filesystem").
Least-Privilege Enforcement Block manifests with excessive scopes (e.g., * in filesystem paths).

Architecture

MCP-Forge/
├── packages/
│   └── security/        # SAML/OAuth adapters, policy engine
└── apps/
    └── api/               # Audit trail API

🗺️ Phase 7: Ecosystem Growth

Goals

  • Incentivize maintainers to publish high-quality MCP servers.
  • Curate collections and highlight popular packages.

Deliverables

Component Description
Stars/Badges Let users star packages; display badges (e.g., "Top 10%", "Verified").
Maintainer Bounties Reward maintainers for high trust scores, installs, or documentation.
Curated Collections Group packages by domain (e.g., "Web Search", "Filesystem Tools").
"Works with X" Badges Show compatibility with clients (e.g., "Works with Ollama", "Works with LM Studio").

Architecture

MCP-Forge/
├── packages/
│   └── ecosystem/       # Bounty system, collection manager
└── apps/
    └── web/               # Stars/badges UI, curated collections page

🗺️ Phase 8: Client Diversity

Goals

  • Support non-OpenAI clients (Ollama, LM Studio, LocalAI).
  • Expand the compatibility matrix and install generator.

Deliverables

Component Description
Ollama Config Generator Generate Modelfile and config.json for Ollama.
LM Studio Config Generator Generate config.yaml for LM Studio.
LocalAI Config Generator Generate config.yaml for LocalAI.
Compatibility Matrix Updates Add rows for Ollama, LM Studio, LocalAI.

Architecture

MCP-Forge/
└── packages/
    └── client-templates/  # New config generators

🗺️ Phase 9: Advanced MCP Features

Goals

  • Support advanced MCP features (roots, sampling, structured outputs) in the sandbox.
  • Validate structured outputs and progress/cancellation.

Deliverables

Component Description
Roots Support Allow sandboxed access to specific filesystem roots.
Sampling Support Test sampling endpoints in the sandbox.
Structured Output Validation Validate JSON Schema compliance for tool outputs.
Progress/Cancellation Support progress updates and request cancellation in the sandbox.

Architecture

MCP-Forge/
├── packages/
│   └── runtime/         # Roots/sampling support in probe.py
└── apps/
    └── web/               # Sandbox UI updates for advanced features

🗺️ Phase 10: Offline Mode

Goals

  • Support air-gapped environments and offline validation.
  • Enable local-first registry mirroring.

Deliverables

Component Description
Air-Gapped Registry Mirroring Sync registry data to a local database for offline use.
Offline Validation Validate manifests without network access.
Local-First Mode Run MCP Forge entirely locally (no cloud dependencies).

Architecture

MCP-Forge/
├── cli/
│   └── mcp-mirror       # Registry mirroring CLI
└── packages/
    └── offline/          # Offline validation logic

🗺️ Phase 11: Automation

Goals

  • Integrate MCP Forge into CI/CD pipelines.
  • Automate manifest validation and trust scoring.

Deliverables

Component Description
GitHub/GitLab CI/CD Integration Validate manifests on PRs; block merges for critical issues.
Automatic Manifest Validation Run mcp-validate on every push to main.
PR Checks Comment on PRs with trust score and security findings.

Architecture

MCP-Forge/
├── .github/
│   └── workflows/       # GitHub Actions workflows
└── packages/
    └── ci/               # CI/CD integration logic

🗺️ Phase 12: Documentation

Goals

  • Provide interactive tutorials, API docs, and video guides.
  • Improve CLI man pages and help text.

Deliverables

Component Description
Interactive Tutorials Step-by-step guides for publishing, installing, and testing MCP servers.
API Docs (Swagger/OpenAPI) Auto-generated API documentation for the registry.
Video Guides YouTube/TikTok-style tutorials for key workflows.
CLI Man Pages Comprehensive man pages for mcp-validate, mcp-probe, etc.

Architecture

MCP-Forge/
├── docs/                 # Interactive tutorials, API docs
└── packages/
    └── docs/             # Video scripts, CLI man pages

🗺️ Phase 13: Monetization

Goals

  • Offer premium features for enterprise users.
  • Sustain development with a sustainable business model.

Deliverables

Component Description
Private Registries Host private MCP registries for enterprise customers.
Priority Support Offer SLAs and dedicated support for premium users.
Premium Features "Verified Publisher" badge, advanced analytics, custom domains.

Architecture

MCP-Forge/
├── apps/
│   └── enterprise/     # Private registry backend
└── packages/
    └── monetization/     # Billing, support ticketing

🗺️ Phase 14: Federation

Goals

  • Support mirror registries and team namespaces.
  • Enable private enterprise registries.

Deliverables

Component Description
Mirror Registries Sync registry data across multiple instances.
Team Namespaces Support @team/package naming for organizations.
Upstream Sync Sync public registry data to private mirrors.
Private Enterprise Registries Host private registries for enterprise customers.

Architecture

MCP-Forge/
├── apps/
│   └── federation/     # Federation backend
└── packages/
    └── sync/            # Upstream sync logic

🗺️ Phase 15: AI-Powered Curation

Goals

  • Use AI to recommend packages, auto-generate docs, and improve search.

Deliverables

Component Description
AI-Driven Package Recommendations Recommend packages based on user behavior and domain.
Auto-Generated Docs Generate API docs, examples, and tutorials from manifests.
Smart Search Improve search relevance with NLP and embeddings.

Architecture

MCP-Forge/
├── packages/
│   └── ai/             # AI models for recommendations/docs/search
└── apps/
    └── web/             # Smart search UI, auto-generated docs

✨ Core Features

Feature Status Description
Registry ✅ Phase 1 Searchable catalog with metadata, tags, health status
Verification ✅ Phase 2 Automated checks for manifest validity, protocol support, smoke tests
Trust Signals ✅ Phase 2 Verified publisher badge, signed release info, trust score, security warnings
Local Runtime ✅ Phase 2 Lightweight runner for stdio/Docker/remote servers
Install Generator ✅ Phase 2 One-click export for Claude, OpenAI, VS Code, Docker Compose
Sandbox Tester ✅ Phase 3 Safe test UI with bounded permissions and visible logs
Security Layer ✅ Phase 3 Scope inspection, least-privilege warnings, network policy hints
Compatibility Matrix ✅ Phase 2 Shows client transport/primitive/auth support
Versioned Manifests ✅ Phase 3 Reproducible package metadata for each release (snapshots)
Publisher Tooling ✅ Phase 2 mcp-validate, mcp-probe, mcp-score, mcp-snapshot CLI tools
Performance Benchmarking 🚧 Phase 4 Latency/throughput metrics, optimization guides
Observability Phase 5 Centralized logging, Prometheus/Grafana dashboards, OpenTelemetry tracing
Enterprise Security Phase 6 SAML/OAuth, audit trails, policy packs, least-privilege enforcement
Ecosystem Growth Phase 7 Stars/badges, maintainer bounties, curated collections
Client Diversity Phase 8 Ollama, LM Studio, LocalAI config generators
Advanced MCP Features Phase 9 Roots/sampling support, structured output validation, progress/cancellation
Offline Mode Phase 10 Air-gapped registry mirroring, offline validation
Automation Phase 11 GitHub/GitLab CI/CD integration, automatic manifest validation
Documentation Phase 12 Interactive tutorials, API docs, video guides, CLI man pages
Monetization Phase 13 Private registries, priority support, premium features
Federation Phase 14 Mirror registries, team namespaces, upstream sync
AI-Powered Curation Phase 15 AI-driven recommendations, auto-generated docs, smart search

🛠️ Getting Started

Prerequisites

  • Node.js 20+
  • Python 3.10+
  • Rust 1.70+
  • Docker (optional, for containerized MCP servers)

Installation

# Clone the repository
git clone https://github.com/Luv-Goel/MCP-Forge.git
cd MCP-Forge

# Install dependencies
npm install

# Build the CLI tools
cd cli && pip install -e .

# Start the registry API
cd ../apps/api && npm run dev

# Start the web UI
cd ../web && npm run dev

Quick Start

# Validate a manifest
mcp-validate mcp.package.json

# Probe a local MCP server
mcp-probe mcp.package.json

# Generate an install config
mcp-generate mcp.package.json --client claude-desktop

🤝 Contributing

We welcome contributions! See CONTRIBUTING.md for guidelines.

Ways to Contribute

  • Publish MCP Servers: Add your MCP server to the registry.
  • Improve Documentation: Write tutorials, fix typos, or add examples.
  • Build Tools: Create new CLI tools or integrations.
  • Report Bugs: Open issues for bugs or feature requests.
  • Review PRs: Help review and test pull requests.

📜 License

MIT © Luv Goel

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The trusted operating layer for MCP servers — registry, verification, sandbox testing, and install generation for Claude, OpenAI-compatible clients, and custom agent runtimes.

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