How do I use grafeo-mcp?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@grafeo-mcp find all Person nodes with name 'Alice'" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

grafeo-mcp

Official

by GrafeoDB

Overview Schema Related Servers Score Discussions

Python

Hybrid

codecov PyPI License

grafeo-mcp

MCP server that exposes GrafeoDB - an embedded graph database - to AI agents via the Model Context Protocol.

One install, zero infrastructure. The MCP server is the database.

Features

23 tools - graph CRUD, GQL queries, batch import, full-text search, vector search, MMR, hybrid retrieval, PageRank, Dijkstra, Louvain and more
3 resources - graph://schema, graph://stats, graph://nodes/{id}
4 workflow prompts - guide agents through exploration, knowledge extraction, graph analysis and similarity search
GQL with Cypher auto-normalization - agents trained on Cypher syntax work out of the box
Schema-first - agents discover the graph structure before querying
Token-aware - all tools have limit params and truncate large results
Embedded - no separate database server to manage

Quickstart

# Install
uv tool install grafeo-mcp

# Or with pip
pip install grafeo-mcp

Claude Desktop

Add to claude_desktop_config.json:

{
  "mcpServers": {
    "grafeo": {
      "command": "grafeo-mcp",
      "env": {
        "GRAFEO_DB_PATH": "/path/to/your/graph.db"
      }
    }
  }
}

Claude Code

Add to .mcp.json in your project root:

{
  "mcpServers": {
    "grafeo": {
      "command": "grafeo-mcp",
      "env": {
        "GRAFEO_DB_PATH": "./graph.db"
      }
    }
  }
}

VS Code / Copilot

Add to .vscode/mcp.json:

{
  "servers": {
    "grafeo": {
      "command": "grafeo-mcp",
      "env": {
        "GRAFEO_DB_PATH": "${workspaceFolder}/graph.db"
      }
    }
  }
}

HTTP transport

For remote or multi-client setups:

grafeo-mcp streamable-http

Environment Variables

Variable	Description	Default
`GRAFEO_DB_PATH`	Path to the database file. Creates it if it doesn't exist	In-memory

Tools

Query

Tool	Description
`execute_gql`	Run GQL queries (Cypher syntax auto-normalized to GQL)

Graph CRUD & Traversal

Tool	Description
`create_node`	Create a node with labels and properties
`create_edge`	Create a directed edge between two nodes
`get_node`	Retrieve a node by ID
`update_node`	Update properties on an existing node
`delete_node`	Delete a node (with optional detach)
`update_edge`	Update properties on an existing edge
`delete_edge`	Delete an edge by ID
`get_neighbors`	Explore a node's neighborhood (1-hop)
`search_nodes_by_label`	Find nodes by label with pagination
`graph_info`	Schema, stats, labels, edge types, indexes

Batch Import

Tool	Description
`batch_import`	Bulk-create nodes and edges from JSON arrays

Full-Text Search

Tool	Description
`create_text_index`	Create a full-text search index on a property
`search_text`	Keyword search over indexed string properties

Vector Search

Tool	Description
`vector_search`	k-NN similarity search (HNSW)
`mmr_search`	Diversity-aware search (Maximal Marginal Relevance)
`create_vector_index`	Create HNSW index on a label + property
`vector_graph_search`	Hybrid: vector search + graph neighborhood expansion

Graph Algorithms

Tool	Description
`pagerank`	Rank nodes by importance
`dijkstra`	Shortest weighted path between two nodes
`louvain`	Community detection (Louvain modularity)
`betweenness_centrality`	Find bridge/bottleneck nodes
`connected_components`	Find disconnected subgraphs

Resources

URI	Description
`graph://schema`	Rich schema: labels, properties, edge types
`graph://stats`	Counts, memory, disk, config info
`graph://nodes/{node_id}`	Node details + connection summary

Prompts

Prompt	Description
`explore_graph`	Guided exploration of the graph structure
`knowledge_extraction`	Extract entities and relationships from text
`graph_analysis`	Structural analysis: communities, PageRank, hubs
`similarity_search`	Vector-powered semantic search with graph context

Which tool when?

I want to...	Use this tool	Not this
Add a single node	`create_node`	`execute_gql`, `batch_import`
Add a single edge	`create_edge`	`execute_gql`
Load many nodes and edges at once	`batch_import`	`create_node` in a loop
Look up a node by ID	`get_node`	`execute_gql`
Update a node's properties	`update_node`	`execute_gql`
Delete a node	`delete_node`	`execute_gql`
Update an edge's properties	`update_edge`	`execute_gql`
Delete an edge	`delete_edge`	`execute_gql`
Browse nodes of a type	`search_nodes_by_label`	`execute_gql`
Explore one hop from a node	`get_neighbors`	`execute_gql`
Run a complex or multi-hop query	`execute_gql`	multiple `get_neighbors`
Search by keyword in text	`search_text`	`execute_gql`
Find similar nodes by embedding	`vector_search`	`execute_gql`
Find similar nodes + graph context	`vector_graph_search`	`vector_search` + `get_neighbors`
Find the most important nodes	`pagerank`	`execute_gql`
Find shortest path between two nodes	`dijkstra`	`execute_gql`
Detect communities	`louvain`	`execute_gql`
Understand the graph before querying	`graph_info`	`search_nodes_by_label`

Batch reference syntax

The batch_import tool lets edges reference nodes created in the same batch using @N notation, where N is the zero-based index into the nodes array:

batch_import(
    nodes=[
        {"labels": ["Person"], "properties": {"name": "Alice"}},  # @0
        {"labels": ["Person"], "properties": {"name": "Bob"}},    # @1
    ],
    edges=[
        {"source_ref": "@0", "target_ref": "@1", "edge_type": "KNOWS"},
    ],
)

You can also mix batch references with existing node IDs: {"source_ref": "@0", "target_ref": 42, ...}.

Cypher normalization

The execute_gql tool automatically normalizes common Cypher syntax to GQL so agents trained on Cypher work out of the box. Currently the following transformations are applied:

Cypher keyword	GQL equivalent
`CREATE`	`INSERT`

Keywords that are shared between Cypher and GQL (such as MATCH, RETURN, WHERE, WITH, LIMIT, DETACH DELETE) pass through unchanged. Cypher-only keywords like MERGE or OPTIONAL MATCH are not supported and will produce a clear error message from the query engine.

Development

git clone https://github.com/GrafeoDB/grafeo-mcp
cd grafeo-mcp
uv sync
uv run pytest          # Run tests
uv run ruff check .    # Lint
uv run ruff format .   # Format
uv run ty check        # Type check

License

Apache-2.0

Install Server

license - permissive license

quality

maintenance

How are these scores calculated?

Maintenance

–Maintainers

–Response time

3wRelease cycle

4Releases (12mo)

Commit activity

Resources

GitHub Repository

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grafeo-mcp

Features

Quickstart

Claude Desktop

Claude Code

VS Code / Copilot

HTTP transport

Environment Variables

Tools

Query

Graph CRUD & Traversal

Batch Import

Full-Text Search

Vector Search

Graph Algorithms

Resources

Prompts

Which tool when?

Batch reference syntax

Cypher normalization

Development

See Also

License

Maintenance

Resources

Looking for Admin?

Tools

Related MCP Servers

FalkorDB MCP Serverofficial

M.I.M.I.R - Multi-agent

Logseq MCP Server

MCP Context Graph

Related MCP Connectors

Latest Blog Posts

MCP directory API