What are the runtime dependencies for Scaffold?
Scaffold requires Neo4j and ChromaDB to be running in Docker on a shared network before the MCP server container starts.

@Beer-Bears
Basic information
Scaffold is a specialized RAG system that transforms entire codebase into a living knowledge graph, capturing the deep structural relationships between files, classes, and functions. This provides AI agents with the crucial context to accurately understand, maintain, and reason a
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"Scaffold": {
"command": "docker",
"args": [
"run",
"--rm",
"--name",
"scaffold-mcp",
"-p",
"8000:8080",
"-v",
"${PROJECT_PATH}:/app/codebase",
"-e",
"CHROMA_SERVER_HOST=${CHROMA_SERVER_HOST}",
"-e",
"CHROMA_SERVER_PORT=${CHROMA_SERVER_PORT}",
"-e",
"CHROMA_COLLECTION_NAME=${CHROMA_COLLECTION_NAME}",
"-e",
"NEO4J_USER=${NEO4J_USER}",
"-e",
"NEO4J_PASSWORD=${NEO4J_PASSWORD}",
"-e",
"NEO4J_URI=${NEO4J_URI}",
"-t",
"ghcr.io/beer-bears/scaffold:latest"
],
"env": {
"CHROMA_SERVER_HOST": "<CHROMA_HOST>",
"CHROMA_SERVER_PORT": "<CHROMA_PORT>",
"CHROMA_COLLECTION_NAME": "scaffold_data",
"NEO4J_USER": "<NEO4J_USER>",
"NEO4J_PASSWORD": "<NEO4J_PASSWORD>",
"NEO4J_URI": "bolt://<NEO4J_USER>:<NEO4J_PASSWORD>@<NEO4J_HOST>:NEO4J_PORT>",
"PROJECT_PATH": "<PATH_TO_YOUR_PROJECT>"
}
}
}
}Tool list not available yet
This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
Scaffold is a specialized Retrieval-Augmented Generation (RAG) system that provides deep, structural understanding of large codebases to LLMs and AI agents. It transforms source code into a living knowledge graph, enabling precise, context-aware interactions. This MCP server allows clients like Cursor to interface with the Scaffold knowledge graph to construct, maintain, and reason about complex software projects.
First, run the required database dependencies (Neo4j and ChromaDB) in Docker on a shared network. Then, configure your MCP client (e.g., mcp.json in Cursor) with a Docker command and environment variables that point to your databases and the absolute path to your codebase. The server exposes a single tool get_code_entity_information that can be invoked from the AI agent.
PaymentService) does.save_graph_to_db).FileNode is and which other methods use it.Scaffold requires Neo4j and ChromaDB to be running in Docker on a shared network before the MCP server container starts.
Ensure the database containers (`scaffold-neo4j` and `scaffold-chromadb`) are running and all three containers are on the same Docker network. Also verify that the user, password, and hostnames in the environment variables match the running databases.
The `PROJECT_PATH` environment variable must be an absolute path on your host machine. Relative paths (like `.` or `~/`) may not work correctly.
Data is stored in the Neo4j graph database and ChromaDB vector store, both running in Docker containers with persistent volumes (`neo4j_data` and `chroma_data`).
Scaffold runs as a Docker container that exposes a port (8000 mapped to container port 8080) for MCP communication over HTTP.

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