OpenModels MCP Registry MCP server
Commit Oct 24, 2026Provides a searchable catalog of MCP servers with structured metadata, tools, resources, and installation configurations for AI agents.
Also known as openmodelsrun/mcp
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- Oct 24, 2026
- License
- MIT
What is OpenModels MCP Registry MCP?
OpenModels MCP Registry provides a searchable catalog of MCP servers with structured metadata, tools, resources, and installation configurations for AI agents.
Summary generated from the project's README
About OpenModels MCP Registry MCP server
This registry serves as a community-maintained catalog for Model Context Protocol servers, designed to help developers extend AI agents with specific tools, resources, and prompts. It organizes hundreds of server entries into eleven distinct categories, including Development, DevOps, and Database. Users can browse the collection through a web interface or by exploring YAML files directly within the repository.
Each entry provides essential technical details such as tool definitions with input schemas, installation configurations, and transport protocols like stdio, sse, or http-streaming. The registry is built to support various client setups, offering configuration snippets for IDEs like Cursor, Windsurf, and VS Code, as well as Claude Code and Gemini CLI. By providing structured metadata and validated schemas, it ensures that developers can easily find and integrate the right capabilities into their AI workflows.
What you can do with it
- 1Configure IDE integrationsAn engineer can obtain ready-to-use configuration snippets to connect an MCP server to their preferred development environment.
- 2Automate server installationUsers can quickly copy the necessary commands to install a new server into their local environment.
- 3Contribute new server definitionsCommunity members can add their own MCP servers to the registry by following a standardized YAML template.
Written from the project's README. Every use case is checked against a quote from it.
README
View on GitHubOpenModels MCP Server Registry
A community-maintained registry of MCP (Model Context Protocol) servers — structured, searchable, and integrated with the OpenModels ecosystem.
Stats
| Metric | Count |
|---|---|
| Servers | 230 |
| Categories | 11 |
| Transport types | 3 (stdio, sse, http-streaming) |
What is this?
This registry catalogs MCP servers that extend AI agents with tools, resources, and prompts. Each server entry includes:
- Description — what the server does and what capabilities it exposes
- Tools — available tool definitions with input schemas
- Resources & Prompts — exposed resources and prompt templates
- Install config — how to install and run the server
- Metadata — category, tags, transport protocols, author, license
Directory Structure
mcp/
├── servers/ # One YAML file per MCP server
│ ├── _template.yaml # Template for contributors
│ ├── arxiv.yaml
│ ├── aws-docs.yaml
│ ├── brave-search.yaml
│ ├── cloudflare.yaml
│ ├── context7.yaml
│ ├── docker.yaml
│ ├── elasticsearch.yaml
│ ├── exa.yaml
│ ├── expo.yaml
│ ├── fetch.yaml
│ ├── figma.yaml
│ ├── firecrawl.yaml
│ ├── filesystem.yaml
│ ├── git.yaml
│ ├── github.yaml
│ ├── grafana.yaml
│ ├── huggingface.yaml
│ ├── jira.yaml
│ ├── jupyter.yaml
│ ├── kubernetes.yaml
│ ├── linear.yaml
│ ├── memory.yaml
│ ├── mongodb.yaml
│ ├── neon.yaml
│ ├── notion.yaml
│ ├── perplexity.yaml
│ ├── playwright.yaml
│ ├── postgres.yaml
│ ├── puppeteer.yaml
│ ├── qdrant.yaml
│ ├── redis.yaml
│ ├── sentry.yaml
│ ├── sequential-thinking.yaml
│ ├── slack.yaml
│ ├── sqlite.yaml
│ ├── stripe.yaml
│ ├── supabase.yaml
│ ├── tavily.yaml
│ ├── time.yaml
│ ├── vercel.yaml
│ ├── vscode.yaml
│ ├── xcode.yaml
│ ├── aws.yaml
│ ├── terraform.yaml
│ ├── datadog.yaml
│ ├── posthog.yaml
│ ├── resend.yaml
│ ├── twilio.yaml
│ ├── clickhouse.yaml
│ └── chromadb.yaml
├── categories/
│ └── categories.yaml # Category definitions
├── schemas/
│ └── server.schema.json # JSON Schema (Draft 7) for validation
├── validate.py # Validation script
├── requirements.txt # Python dependencies (PyYAML, jsonschema)
├── CONTRIBUTING.md # Contribution guide
├── CHANGELOG.md # Version history
├── LICENSE # MIT
├── README.md # This file
└── VERSION # Current version (1.11.0)
Quick Start
Browse servers
Visit openmodels.run/mcp to search, filter, and compare MCP servers with a web UI.
Or explore the YAML files directly in the servers/ directory.
Install a server
Each server detail page at openmodels.run/mcp/{server-id} includes an Install MCP server button that copies the install command to your clipboard and provides IDE-specific configuration snippets.
Add a new server
- Fork this repository
- Copy
servers/_template.yamltoservers/{your-server-id}.yaml - Fill in your server details (see CONTRIBUTING.md)
- Validate locally:
python validate.py - Submit a pull request
Server Format
Each server is a YAML file validated against a JSON Schema:
id: github
name: GitHub MCP Server
description: >
Provides access to the GitHub API through the Model Context Protocol...
author:
name: GitHub
github: github
repository: https://github.com/github/github-mcp-server
transport:
- stdio
- http-streaming
category: Development
tags:
- github
- git
- version-control
tools:
- name: create_issue
description: Create a new issue in a GitHub repository.
input_schema:
type: object
properties:
owner:
type: string
repo:
type: string
title:
type: string
required: [owner, repo, title]
install:
npm: "@github/github-mcp-server"
command: docker
args: ["run", "-i", "--rm", "-e", "GITHUB_PERSONAL_ACCESS_TOKEN", "ghcr.io/github/github-mcp-server"]
env_vars:
- name: GITHUB_PERSONAL_ACCESS_TOKEN
description: GitHub personal access token for API authentication
required: true
license: MIT
version: "1.0.5"
stars: 30200
created_at: "2024-11-25T00:00:00.000Z"
updated_at: "2026-05-21T00:00:00.000Z"
Selected servers
The table below highlights representative entries. See the servers/ directory for
the complete 207-server registry.
| Server | Category | Author | Transport |
|---|---|---|---|
| ArXiv | Research | Joe Blazick | stdio, http-streaming |
| AWS Docs | Development | AWS Labs | stdio |
| Brave Search | Research | Brave | stdio |
| Cloudflare | Cloud | Cloudflare | stdio |
| Context7 | Development | Upstash | stdio, http-streaming |
| Docker | DevOps | Docker | stdio |
| Elasticsearch | Database | Elastic | stdio, http-streaming |
| Exa | Research | Exa Labs | stdio |
| Expo | Development | Expo | stdio, http-streaming |
| Fetch | Development | Anthropic | stdio |
| Figma | Development | Figma | stdio, http-streaming |
| Firecrawl | Research | Mendable | stdio |
| Filesystem | Filesystem | Anthropic | stdio |
| Git | Development | Anthropic | stdio |
| GitHub | Development | GitHub | stdio, http-streaming |
| Grafana | DevOps | Grafana Labs | stdio, sse |
| Hugging Face | AI | Hugging Face | stdio, http-streaming |
| Jira (Atlassian) | Productivity | Atlassian | stdio, http-streaming |
| Jupyter | Development | Datalayer | stdio |
| Kubernetes | DevOps | Marc Nuri | stdio, http-streaming |
| Linear | Productivity | Linear | stdio |
| Memory | AI | Anthropic | stdio |
| MongoDB | Database | MongoDB | stdio, http-streaming |
| Neon | Database | Neon | stdio |
| Notion | Productivity | Notion | stdio |
| Perplexity | Research | Perplexity AI | stdio, http-streaming |
| Playwright | Browser Automation | Microsoft | stdio |
| PostgreSQL | Database | Anthropic | stdio |
| Puppeteer | Browser Automation | Anthropic | stdio |
| Qdrant | Database | Qdrant | stdio, sse, http-streaming |
| Redis | Database | Anthropic | stdio |
| Sentry | DevOps | Sentry | stdio |
| Sequential Thinking | AI | Anthropic | stdio |
| Slack | Communication | Anthropic | stdio |
| SQLite | Database | Anthropic | stdio |
| Stripe | Development | Stripe | stdio |
| Supabase | Database | Supabase | stdio |
| Tavily | Research | Tavily | stdio |
| Time | Productivity | Anthropic | stdio |
| Vercel | DevOps | Vercel | stdio, http-streaming |
| VSCode | Development | acomagu | stdio |
| Xcode | Development | Apple | stdio |
| AWS | Cloud | AWS Labs | stdio |
| ChromaDB | Database | Chroma | stdio |
| ClickHouse | Database | ClickHouse | stdio |
| Datadog | DevOps | Datadog | stdio |
| PostHog | Productivity | PostHog | stdio |
| Resend | Communication | Resend | stdio |
| Terraform | Cloud | HashiCorp | stdio |
| Twilio | Communication | Twilio | stdio |
Categories
| Category | Description |
|---|---|
| Development | Code generation, testing, debugging, and software development tools |
| Productivity | Task management, note-taking, workflow automation |
| Database | Database querying, schema management, and data manipulation |
| DevOps | CI/CD, infrastructure management, monitoring |
| AI | Machine learning, model management, and AI utilities |
| Research | Web search, knowledge retrieval, and information gathering |
| Browser Automation | Web scraping, browser control, and automated testing |
| Communication | Messaging, email, notifications, and collaboration |
| Filesystem | File operations, directory management, and local storage |
| Cloud | Cloud provider APIs, serverless functions, and cloud storage |
| Security | Authentication, encryption, and vulnerability scanning |
Validation
All server definitions are validated against JSON Schema on every PR:
pip install -r requirements.txt
python validate.py
Validation checks:
- YAML syntax
- Schema conformance (required fields, types, enums, patterns)
- No duplicate IDs across all server definitions
- Filename matches the
idfield
CI Integration
A GitHub Actions workflow runs validation automatically on every pull request that modifies files in servers/, schemas/, or validate.py. PRs that fail validation cannot be merged.
Contributing
We welcome contributions! See CONTRIBUTING.md for the full guide.
Quick steps:
- Fork this repository
- Copy
servers/_template.yamland fill in your server details - Run validation:
python validate.py - Submit a pull request
Integration with OpenModels
MCP servers are ingested into the OpenModels platform and available via:
- Web UI — browse, filter, search, and compare at openmodels.run/mcp
- API — query programmatically via
/api/v1/mcp/servers - IDE configs — generate connection snippets for Claude Code, Cursor, Windsurf, Gemini CLI, Kiro, and VS Code
- Install button — one-click copy of install commands on each server detail page
License
MIT
OpenModels MCP Registry MCP questions
How can I install an MCP server from this registry?
You can use the 'Install MCP server' button on the server detail pages to copy install commands and IDE-specific configuration snippets.
What transport types are supported by the servers in this registry?
The registry includes servers using stdio, sse, and http-streaming transport types.
Can I add my own MCP server to the registry?
Yes, you can contribute by forking the repository, creating a new YAML file from the template, and submitting a pull request.