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mcp server

mcp-fabric

Composable tool mesh for MCP ecosystems — server registry, capability normalization, trust policies, capability routing, and audit for agentic tool platforms.

deghosal-2026/mcp-fabriccommunitylistedunreviewed

Set up

Runs on your computer. Pick your agent and operating system.

Before you start

  • uv (`curl -LsSf https://astral.sh/uv/install.sh | sh`)
~/Library/Application Support/Claude/claude_desktop_config.json
{
  "mcpServers": {
    "deghosal-2026-mcp-fabric": {
      "command": "uvx",
      "args": [
        "mcp-fabric-toolmesh"
      ]
    }
  }
}

same format Cursor, GitHub Copilot CLI, Junie, JetBrains AI Assistant, Augment (Auggie CLI), Factory Droid, Kiro, Devin CLI +12

Values in angle brackets are placeholders. Restart Claude Desktop after editing its config.Claude Desktop docs

README

synced Oct 26, 2026

MCP Fabric

CI License: MIT Python 3.12+ PyPI OpenSSF Best Practices OpenSSF Scorecard Ruff Type checked Contributor Covenant

A control plane for AI agents — register MCP servers, normalize tools into capabilities, control access with policies and trust levels, require human approval for sensitive actions, and audit everything.

MCP solves one important problem: a standard interface for AI tools and data. It does not solve the next problem that appears immediately after success: tool ecosystem sprawl.

MCP Fabric is that missing layer — the dashboard where platform teams connect, organize, control, review, and monitor every tool their agents use.

The Problem

Once a team adds multiple MCP servers, several hard questions emerge:

  • Which tools should be exposed to which agents?
  • How should overlapping capabilities be described?
  • What trust level should be assigned to each server?
  • Which agents get access to which tools — and who needs to approve?
  • How should a platform team audit and govern usage across the whole tool ecosystem?

What's New in v0.4.0 — Trust Posture, Admissions & Review Resilience

Full changelog: docs/CHANGELOG.md

v0.4.0 delivers a trust posture + resilience release across four milestones:

M1 — Pack Cohesion & Adversarial Fuzz

  • Pack cohesion score — similarity-dispersion cohesion axis on the Trust Posture dashboard; tight "semantic bands" are flagged with a per-resource identity recommendation
  • λ-clustered nighttime fuzz harness — models the similarity-targeting attacker (catch collapse) against real pack layouts, independent of PR-gate CI

M2 — Permissions & Policy Feedback

  • Read-only vs destructive tool classification enforced at the request boundary
  • Structured denial feedback — DenialResult returned to agents (branch, don't blind-retry)
  • Many-to-one collision detection with a mandatory review gate and origin-aware OPA denials

M3 — Review Queue Resilience

  • Fail-closed re-inspection — timeout/unreachable never recorded as unchanged
  • External staleness watchdog with heartbeat + dead-man switch
  • Queue prioritization — unreachable items separated from genuine schema changes, with bulk retire

M4 — HITL Approval Fatigue

  • Reversibility split — reads/undo‑able actions auto-approved; writes prompted
  • Bulk approve with explicit anomaly markers
  • Scoped, expiring approval envelopes burned down by a deterministic validator

Key resources:

Quick Start

# Install from PyPI
pip install mcp-fabric-toolmesh

# Clone and start the full stack (Docker)
git clone https://github.com/deghosal-2026/mcp-fabric.git
cd mcp-fabric
docker-compose up -d

# Or run locally without Docker:
poetry install && cd ui && npm install && cd ..
poetry run uvicorn api.main:app --reload &
cd ui && npm run dev
ServiceURL
APIhttp://localhost:8000
API Docs (Swagger)http://localhost:8000/docs
Admin UIhttp://localhost:3000
Metricshttp://localhost:8000/v1/metrics
Healthhttp://localhost:8000/health

Documentation

GuideDescription
👤 Admin UI User GuideWalkthrough of all UI pages with screenshots
📄 Product Requirements (PRD)29 user journeys, persona definitions, product scope
📐 Technical SpecificationFull architecture, DB schema, API contract, OPA policies
🏗️ ArchitectureSystem design, data flow, component interfaces
🧪 UI Test PlanUI test strategy: 145 vitest tests
🧪 Docker Test PlanE2E test strategy: Playwright + curl + 19 screenshots
🛠️ Development GuideLocal setup, testing, migrations, Docker Compose
🚀 Deployment GuideDocker Compose deploy, env vars, backup/restore, blue-green upgrade
⚙️ Configuration ReferenceAll 25 env vars with defaults, feature flags, production checklist
📊 Monitoring GuidePrometheus metrics, Grafana dashboard, Alertmanager, OTel tracing
🔒 Security GuideAuth model, password policy, MFA, token lifecycle, RBAC, audit
❓ Troubleshooting GuideCommon issues: API, health checks, OPA, Redis, CORS, DB migrations
📝 ChangelogVersion history and release notes

What MCP Fabric Does

MCP Fabric is a control plane for AI agents. It sits between your MCP servers and the agents that consume them, giving platform teams a single dashboard to manage the full lifecycle:

1. Register servers → 2. Define capabilities → 3. Set policies
→ 4. Create agent classes + tokens → 5. Bundle into packs
→ 6. Assign packs → 7. Approve gated actions → 8. Audit everything
LayerWhat It Provides
Server RegistryRegister, inspect, and monitor MCP servers. Auto-discover tools from /tools/list. Filter by health, trust, team.
Capability CatalogNormalize raw MCP tools into meaningful capabilities (e.g. deployment:promote). Deprecate with configurable grace periods.
OPA Policy EngineDeploy Rego policies that govern access decisions — trust hierarchy, agent class requirements, namespace isolation.
Agent Classes + TokensDefine agent types (agent:developer) and issue identity tokens (fcp_****). Token shown once at creation.
Capability PacksBundle capabilities and assign them to agent classes. Control which capabilities each class can access.
ApprovalsHuman-in-the-loop for sensitive capabilities. Review requests with full context (agent, capability, server, parameters).
Audit LogImmutable record of every action — capability requests, policy changes, server events. Export for compliance (SOC2, SOX).
AlertsSurface operational issues: server degradation, unreachable servers, unreviewed servers, denial spikes.
Trust PosturePer-agent-class trust levels with color-coded cards. Optimistic UI updates with automatic rollback on error.
Admin User ManagementRBAC with Admin/Editor/Viewer roles. MFA enforcement.

Architecture

Agent → MCP Fabric API → Registry → OPA Policy → Approval Gate → Target MCP Server
                            ↓
                      Audit Pipeline
                            ↓
                     ┌──────────────┐
                     │  Admin UI    │
                     │  (Dashboard, │
                     │   Config,    │
                     │   Monitor)   │
                     └──────────────┘

The Admin UI is the control plane. Platform teams use it to register servers, define capabilities, set policies, manage agent classes, bundle packs, review approvals, monitor alerts, and audit activity — all from a single dashboard.

Stack

  • API: FastAPI
  • Metadata store: PostgreSQL
  • Cache: Redis
  • Policy engine: OPA (Open Policy Agent) Rego policies
  • Telemetry: OpenTelemetry, Tempo, Prometheus, Grafana
  • UI: React
  • Local dev: Docker Compose

Everything runs locally. No enterprise dependencies required.

Roadmap

v0.4.0 — Current (shipped):

  • Trust Posture: pack cohesion score + semantic-band detection (#439)
  • Nightly λ-clustered adversarial resource-confusion fuzz harness (#440)
  • Agent-level permissions — read-only vs destructive tool classification (#445)
  • Structured policy-denial feedback to agents (#443)
  • Many-to-one capability-mapping collision detection + review gate (#441)
  • Fail-closed re-inspection + stale-review age alerts (#444)
  • External staleness watchdog with heartbeat + dead-man switch (#446)
  • Review queue prioritization — unreachable vs genuinely changed (#447)
  • Approval fatigue mitigation — reversibility split + bulk approve + expiring envelopes (#442)

v0.5.0 — Planned:

  • Advanced routing engine (health/latency/fallback-aware)
  • Conflict detection across similar tools
  • Capability-to-tool mapping UI
  • Persistent webhook storage

Gap — Planned:

  • Multi-tenant scopes and namespace isolation
  • Analytics and usage heatmaps
  • Performance benchmarks and caching improvements

GA (v1.0.0) — Planned:

  • Stabilization, security audit, production hardening, and enterprise features

Test Status

| Suite | Tests | Status | |---|---|---|---| | Backend unit (services, middleware, errors, models) | 387 | ✅ Passing | | OPA policy (Rego) | 37 | ✅ Passing | | UI unit/integration (Vitest) | 140 | ✅ Passing | | UI E2E + screenshots (Playwright) | 130 | ✅ Passing | | Docker Compose E2E (curl) | 6 | ✅ Scripts ready | | Total | 700 | |

make test        # Backend unit tests
make test-unit   # Unit tests only
cd ui && npm test  # UI tests
make opa-test    # OPA policy tests

Who It's For

  • Platform teams managing multiple MCP servers
  • Advanced agent builders who need governed tool access
  • Developer experience teams building internal AI tooling platforms
  • OSS builders creating reusable MCP ecosystems

License

MIT


See ROADMAP, GOVERNANCE, and CONTRIBUTING for project direction, governance, and how to contribute.

Resources

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