awesome-llm-apps-mcp
An MCP (Model Context Protocol) server that gives AI assistants access to 160+ AI agent examples from the awesome-llm-apps collection.
Ask "I want to build a finance agent" and get relevant agent ideas, architecture patterns, tech stacks, and actual source code — directly inside Claude, Cursor, or any MCP-compatible tool.
Features
- Search agents by keyword, use case, or technology
- Browse categories: Starter agents, advanced multi-agent teams, RAG, voice, MCP, and more
- Get inspiration: Recommended tech stacks and architecture patterns for your use case
- Read source code: Full Python implementations you can study and adapt
- Zero config: No API keys, no databases — just install and go
Installation
pip install awesome-llm-apps-mcp
Or run directly with uvx:
uvx awesome-llm-apps-mcp
Configuration
Claude CLI
claude mcp add awesome-llm-apps -- uvx awesome-llm-apps-mcp
Cursor (.cursor/mcp.json)
{
"mcpServers": {
"awesome-llm-apps": {
"command": "uvx",
"args": ["awesome-llm-apps-mcp"]
}
}
}
Claude Desktop (claude_desktop_config.json)
{
"mcpServers": {
"awesome-llm-apps": {
"command": "uvx",
"args": ["awesome-llm-apps-mcp"]
}
}
}
Tools
search_ai_agents
Find agents by keyword or use case. Returns lightweight summaries with relevance scores.
search_ai_agents("finance agent")
search_ai_agents("RAG with ChromaDB", category="rag_tutorials")
search_ai_agents("multi-agent team", limit=5)
get_agent_details
Get full documentation, features, and tech stack for a specific agent.
get_agent_details("starter-ai-agents-xai-finance-agent")
get_agent_source_code
Get the actual Python source files for an agent.
get_agent_source_code("starter-ai-agents-xai-finance-agent")
list_agent_categories
Browse all categories with agent counts.
list_agent_categories()
Categories:
starter_ai_agents— Single-agent apps with focused functionalityadvanced_ai_agents— Multi-agent systems and complex applicationsrag_tutorials— Retrieval-Augmented Generation implementationsadvanced_llm_apps— Advanced LLM application patternsai_agent_framework_crash_course— Framework tutorials (Google ADK, OpenAI SDK)awesome_agent_skills— Reusable agent skill definitionsmcp_ai_agents— Model Context Protocol agent implementationsvoice_ai_agents— Voice/audio-based agent applications
get_agent_inspiration
Get high-level suggestions for a use case, including recommended tech stack and architecture.
get_agent_inspiration("a customer support chatbot with RAG")
Development
git clone <repo>
cd agent-mcp
pip install -e ".[dev]"
pytest tests/
Rebuilding the catalog
If you want to rebuild catalog.json from a local copy of awesome-llm-apps:
python scripts/build_catalog.py /path/to/awesome-llm-apps
Testing with MCP Inspector
npx @modelcontextprotocol/inspector awesome-llm-apps-mcp
License
MIT
Metadata
Release files for awesome-llm-apps-mcp 0.1.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| awesome_llm_apps_mcp-0.1.0.tar.gz | 706.0 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| awesome_llm_apps_mcp-0.1.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 1.4 MB
Release files / awesome_llm_apps_mcp-0.1.0.tar.gz
| Download URL | awesome_llm_apps_mcp-0.1.0.tar.gz |
|---|---|
| Size | 706.0 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
e55906cece468bd6eab7909178255a983da44dd70b8acc42806cc9ce5686b797
|
|
BLAKE2b-256 checksum How to use checksums |
262ca35d12d2988b37c0df5301a477583a759105a7826c6d0e12a82aecaf945e
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.13.5
|
Release files / awesome_llm_apps_mcp-0.1.0-py3-none-any.whl
| Download URL | awesome_llm_apps_mcp-0.1.0-py3-none-any.whl |
|---|---|
| Size | 705.7 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
9963f2c9b32c5f36f3c0dffefb70a3169b10f97f4ccc924d3ed829ddd386b022
|
|
BLAKE2b-256 checksum How to use checksums |
8fcc6ddaa2afdf1f7f4b44a0178e7efa435718d37b90e6eaba4095fc08c598fd
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.13.5
|
Security for awesome-llm-apps-mcp 0.1.0
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.