AI App
FreeNot checkedA production-ready Python MCP server supporting stdio and Streamable HTTP transports, providing tools for health check, user query normalization, knowledge base
About
A production-ready Python MCP server supporting stdio and Streamable HTTP transports, providing tools for health check, user query normalization, knowledge base search, document retrieval, and RAG prompt construction.
README
A production-ready Python MCP server that supports both stdio and Streamable HTTP transports.
Features
health_check: return server health and runtime configuration.normalize_user_query: normalize user text before retrieval or agent routing.search_knowledge_base: search local.md,.txt, and.jsonfiles.get_document: read a safe document from the configured knowledge directory.build_rag_prompt: build a grounded RAG prompt.config://runtime: expose safe runtime configuration.rag_answer_prompt: reusable RAG prompt template.
Install
cd D:\projects\codex\single\mcp
python -m venv .venv
.\.venv\Scripts\Activate.ps1
pip install -e ".[dev]"
Copy-Item .env.example .env
Transport 1: stdio
Use stdio when an AI client starts this MCP server as a local child process.
ai-app-mcp --transport stdio
Equivalent module command:
python -m ai_app_mcp.server --transport stdio
Client configuration example:
{
"mcpServers": {
"ai-app-mcp": {
"command": "python",
"args": [
"-m",
"ai_app_mcp.server",
"--transport",
"stdio"
],
"env": {
"MCP_KNOWLEDGE_DIR": "D:/projects/codex/single/mcp/knowledge"
}
}
}
}
In stdio mode, stdout is used for MCP protocol messages. Logs are written to stderr.
Transport 2: Streamable HTTP
Use Streamable HTTP for MCP Inspector, HTTP debugging, or service-to-service integration.
ai-app-mcp --transport streamable-http --host 127.0.0.1 --port 8000
Equivalent module command:
python -m ai_app_mcp.server --transport streamable-http --host 127.0.0.1 --port 8000
MCP endpoint:
http://127.0.0.1:8000/mcp
Do not open this endpoint directly as a normal web page. It is a JSON-RPC MCP endpoint and requires an MCP client.
Debug With MCP Inspector
Start this MCP server:
ai-app-mcp --transport streamable-http --host 127.0.0.1 --port 8000
Start Inspector:
npx -y @modelcontextprotocol/inspector
Open:
http://localhost:6274
Use:
Transport: Streamable HTTP
URL: http://127.0.0.1:8000/mcp
Environment
Copy .env.example to .env and adjust values:
MCP_SERVER_NAME=ai-app-mcp
MCP_LOG_LEVEL=INFO
MCP_KNOWLEDGE_DIR=./knowledge
MCP_MAX_TEXT_CHARS=12000
Knowledge Directory
By default, the server reads files from ./knowledge. Only .md, .txt, and .json files are allowed. Paths are resolved safely so clients cannot read files outside the knowledge directory.
Test
pytest
from github.com/yh008/Mcp
Install AI App in Claude Desktop, Claude Code & Cursor
unyly install ai-app-mcpInstalls into Claude Desktop, Claude Code, Cursor & VS Code — handles npx, uvx and build-from-source repos for you.
First time? Get the CLI: curl -fsSL https://unyly.org/install | sh
Or configure manually
Run in your terminal:
claude mcp add ai-app-mcp -- uvx --from git+https://github.com/yh008/Mcp ai-app-mcpFAQ
Is AI App MCP free?
Yes, AI App MCP is free — one-click install via Unyly at no cost.
Does AI App need an API key?
No, AI App runs without API keys or environment variables.
Is AI App hosted or self-hosted?
Self-hosted: the server runs locally on your machine via the install command above.
How do I install AI App in Claude Desktop, Claude Code or Cursor?
Open AI App on unyly.org, pick your client tab (Claude Desktop, Claude Code, Cursor) and press Install — the config is generated automatically, no JSON editing.
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