graforest-mcp 0.1.1

Graforest MCP Server — Build, populate, and query Knowledge Graphs with AI. 13 tools for knowledge ingestion, search, traversal, and graph management.

Graforest MCP Server

Build knowledge graphs with AI. 13 tools for creating, populating, searching, and exploring knowledge graphs through the Model Context Protocol.

What Is This?

Graforest MCP lets AI agents (Claude, Cursor, VS Code, etc.) build and query knowledge graphs. No database setup. No Neo4j config. Just tell your AI agent what you want to know.

"Create a knowledge graph about organic chemistry and populate it from my notes"
→ 2 minutes later: Searchable knowledge graph with entities and relationships

The AI agent handles intelligence (entity extraction, reasoning). Graforest handles data (storage, search, traversal).

Installation

pip install graforest-mcp

Quick Start

1. Get Your API Key

Visit graforest.ai/settings and create an API key (gf_sk_...).

2. Configure Your AI Agent

VS Code — Add to .vscode/mcp.json:

{
  "servers": {
    "graforest": {
      "command": "uvx",
      "args": ["graforest-mcp"],
      "env": {
        "GRAFOREST_API_KEY": "gf_sk_your_key_here"
      }
    }
  }
}

Cursor — Add to .cursor/mcp.json:

{
  "mcpServers": {
    "graforest": {
      "command": "uvx",
      "args": ["graforest-mcp"],
      "env": {
        "GRAFOREST_API_KEY": "gf_sk_your_key_here"
      }
    }
  }
}

Claude Desktop — Add to claude_desktop_config.json:

{
  "mcpServers": {
    "graforest": {
      "command": "uvx",
      "args": ["graforest-mcp"],
      "env": {
        "GRAFOREST_API_KEY": "gf_sk_your_key_here"
      }
    }
  }
}

Smithery:

npx @smithery/cli install @graforest/mcp

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13 Tools

Provisioning (3 tools)

Tool	Description
create_knowledge_project	Provision a new knowledge graph (Neo4j)
list_knowledge_projects	List all graph projects
delete_knowledge_project	Delete a graph project permanently

Data Write (2 tools)

Tool	Description
add_knowledge_nodes	Bulk create entities (max 500/batch)
add_knowledge_relationships	Bulk create relationships (max 500/batch)

Data Read (6 tools)

Tool	Description
search_knowledge_graph	Full-text search across all node fields
get_knowledge_schema	Get entity types, relationship types, and fields
get_knowledge_statistics	Node and relationship counts by type
traverse_knowledge_graph	Walk connections from any node
list_knowledge_entities	List entities by type (paginated)
get_knowledge_entity	Get a single entity by ID

Ingestion (1 tool)

Tool	Description
ingest_text_content	Prepare text for the 3-call extraction workflow

Utility (1 tool)

Tool	Description
fetch_url_content	Scrape a URL and return clean text

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3-Call Ingestion Workflow

The recommended way to populate a knowledge graph from text:

1. ingest_text_content(project_code, text) → Returns the graph schema + extraction instructions
2. LLM extracts all entities and relationships from the text (guided by the instructions)
3. add_knowledge_nodes + add_knowledge_relationships → Bulk write everything

The AI does the thinking. Graforest stores the results.

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Cloud Deployment (LogicBlok Module)

Graforest MCP deploys as a LogicBlok module through the RationalBloks platform. No kubectl, Docker CLI, or cluster access needed.

Deploy via RationalBloks UI

1. Log in at infra.rationalbloks.com
2. Select the Graforest project → Modules → Deploy Module
3. Settings:
   • Name: graforest-mcp
   • Type: logicblok
   • Repo: https://github.com/graforest/graforest-mcp
   • Dockerfile: Dockerfile (root of repo)
4. Set environment variables:
   • GRAFOREST_RB_API_KEY — Graforest service account key (rb_sk_...)
   • RATIONALBLOKS_MCP_URL — https://logicblok.rationalbloks.com
   • TRANSPORT — http
   • HOST — 0.0.0.0
5. Deploy. The platform handles: clone → build → push → K8s → TLS.

What the Platform Creates

Resource	Value
Namespace	customer-{project_code}-staging
Domain	{module_code}-mod.customersblok.rationalbloks.com
Port	8000 with /health probes
TLS	Auto-provisioned by cert-manager

Dockerfile

The included Dockerfile meets the LogicBlok module contract:

• Port 8000
• /health endpoint
• Non-root user (UID 1000)
• Multi-stage build with UV dependency caching

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Architecture

AI Agent → graforest-mcp → Graph APIs (Neo4j databases)
                         → RationalBloks API (infrastructure provisioning)

• No AI inside the MCP server — the LLM is the intelligence, Graforest is the data layer
• Dual transport: STDIO (local IDEs) + HTTP/SSE (cloud deployment)
• API key auth: gf_sk_ prefix for all Graforest keys

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Resources & Prompts

Resources:

• graforest://docs/getting-started — Quick start guide
• graforest://docs/knowledge-graph — Knowledge graph concepts

Prompts:

• ingest-content — Guided content ingestion workflow
• explore-graph — Guided graph exploration workflow

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Environment Variables

Variable	Required	Default	Description
GRAFOREST_API_KEY	Yes (STDIO)	—	Your Graforest API key
TRANSPORT	No	stdio	Transport mode: stdio or http
PORT	No	8000	HTTP server port
HOST	No	0.0.0.0	HTTP server bind address

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Support

• Website: graforest.ai
• Documentation: graforest.ai/docs
• Email: [e-mail]