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adamchall87

AI Model Registry MCP Server

by adamchall87
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

AI Model Registry

Live AI model registry that polls OpenRouter, HuggingFace, and Ollama Cloud hourly. Provides agents (Hermes, OpenClaw, Claude Code) with up-to-date model information so they never recommend outdated models from stale training data.

Architecture

┌─────────────────────────────────────────────┐
│         AI Model Registry (FastAPI)          │
│                                              │
│  ┌─────────┐  ┌──────────┐  ┌─────────────┐ │
│  │OpenRouter│  │HuggingFace│  │Ollama Cloud │ │
│  │  poller  │  │  poller   │  │   poller    │ │
│  └────┬─────┘  └─────┬─────┘  └──────┬──────┘ │
│       └──────────────┼────────────────┘      │
│                      ▼                        │
│              In-Memory Cache                   │
│                      │                        │
│         ┌────────────┼────────────┐           │
│         ▼            ▼            ▼           │
│    REST API    MCP Server    Hermes Skill      │
│  (port 8000)  (stdio)     (SKILL.md)          │
└─────────────────────────────────────────────┘

Related MCP server: ai-model-selector-mcp

Quick Start

# Clone
git clone <your-repo> ai-model-registry
cd ai-model-registry

# Install
pip install -r requirements.txt

# Run the API server
python -m uvicorn src.server:app --port 8000

# In another terminal, test it
curl http://localhost:8000/
curl http://localhost:8000/models/best?capability=coding
curl http://localhost:8000/models/search?q=kimi

Deploy on VPS (systemd)

# Copy to VPS
scp -r ai-model-registry user@vps:/opt/ai-model-registry

# Install deps
cd /opt/ai-model-registry
pip install -r requirements.txt

# Install service
sudo cp deploy/ai-model-registry.service /etc/systemd/system/
sudo systemctl daemon-reload
sudo systemctl enable --now ai-model-registry

# Verify
curl http://localhost:8000/

MCP Integration (Hermes)

Add to ~/.hermes/config.yaml:

mcp_servers:
  model_registry:
    command: "python3"
    args: ["/opt/ai-model-registry/src/mcp_server.py"]
    env:
      REGISTRY_API_URL: "http://localhost:8000"

Then copy the skill:

cp -r skill /path/to/.hermes/skills/ai-model-registry

Restart Hermes. Tools will appear as:

  • mcp_model_registry_list_models

  • mcp_model_registry_search_models

  • mcp_model_registry_best_models

  • mcp_model_registry_registry_stats

API Endpoints

Endpoint

Description

GET /

Health check + cache info

GET /models

List models with filters (source, capability, min_context, max_input_price, limit, offset)

GET /models/search?q=X

Search by name/id/description

GET /models/best?capability=X

Best models for a capability (coding, vision, tools, reasoning, agent, general, cheapest, largest_context)

GET /models/by-source/{source}

Filter by provider

POST /refresh

Manual refresh

GET /stats

Registry statistics

Environment Variables

Var

Default

Description

POLL_INTERVAL

3600

Seconds between polls (1 hour)

OLLAMA_API_KEY

(empty)

Ollama Cloud API key for full model listing

REGISTRY_API_URL

http://localhost:8000

URL for MCP server to connect to

Data Sources

  • OpenRouter: GET https://openrouter.ai/api/v1/models — 400+ models with pricing

  • HuggingFace: GET https://huggingface.co/api/models — Hub models + inference models

  • Ollama Cloud: GET https://ollama.com/api/tags — Cloud models (API key optional)

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license - not found
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C
maintenance

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Maintenance

–Maintainers
–Response time
–Release cycle
–Releases (12mo)
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