KnowledgeSmith MCP
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@KnowledgeSmith MCPadd my project requirements document to the knowledge graph"
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.
KnowledgeSmith MCP Server
MCP Server for Graphiti memory and document chunking. Previously included RBT document editing tools (now archived).
📦 Archive Notice
RBT Document Editor Tools (Archived 2025-10-09)
The RBT document editing功能已於 2025-10-09 封存,改用原生 Claude Code Read/Edit/Write 工具以降低維護成本和 token 使用。
封存內容:
document_service.py - 文件服務
document_parser.py - 文件解析器
11 個 editor MCP 工具(get_outline, read_content, update_block 等)
templates/ - 文件模板
cache.py - 文件快取
保留功能:
✅ chunking/ - 文件分塊與同步功能
✅ graphiti_tools.py - Graphiti 記憶體功能(8 個工具)
如何恢復封存的代碼:
# 查看封存版本
git show v-with-editor
# 恢復特定檔案
git checkout v-with-editor -- rbt_mcp_server/document_service.py
# 或建立分支使用完整封存版本
git checkout -b restore-editor v-with-editorRelated MCP server: Semantic Cache MCP
🎯 Current Features
Graphiti Knowledge Graph Integration
Intelligent Chunking: Automatically split documents into semantic chunks based on document structure (sections for RBT, H3 headings for Markdown)
Incremental Sync: Only update changed chunks, preserving unchanged content
Neo4j Backend: Store document chunks as episodes in Graphiti knowledge graph
graphiti-memory Compatible: Drop-in replacement with same search_nodes/search_facts API
8 MCP Tools: add_document, search_memory_nodes, search_memory_facts, get_episodes, delete_episode, get_entity_edge, delete_entity_edge, clear_graph
📦 Installation
Prerequisites
1. Setup Neo4j Database
Using Docker (recommended):
docker run \
-p 7474:7474 \
-p 7687:7687 \
-e NEO4J_AUTH=neo4j/your-password \
--name neo4j \
neo4j:latestVerify at: http://localhost:7474
2. Get OpenAI API Key
Required for Graphiti embeddings and graph operations.
Install MCP Server
Option 1: Install from source (uv)
# Clone repository
git clone https://github.com/yourusername/KnowledgeSmith.git
cd KnowledgeSmith
# Install with uv
uv pip install -e .Option 2: Direct installation
uv pip install rbt-mcp-server🚀 Quick Start
1. Configure Claude Desktop
Add to ~/Library/Application Support/Claude/claude_desktop_config.json:
{
"mcpServers": {
"graphiti-memory-server": {
"type": "stdio",
"command": "rbt-mcp-server",
"env": {
"RBT_ROOT_DIR": "/path/to/your/document/root",
"NEO4J_URI": "bolt://localhost:7687",
"NEO4J_USER": "neo4j",
"NEO4J_PASSWORD": "your-password",
"OPENAI_API_KEY": "your-openai-api-key"
}
}
}
}Required Environment Variables:
RBT_ROOT_DIR: Root directory for document comparison (required for add_document tool)NEO4J_URI,NEO4J_USER,NEO4J_PASSWORD: Neo4j database connectionOPENAI_API_KEY: OpenAI API key for Graphiti embeddings
Or use full uv command:
{
"mcpServers": {
"graphiti-memory-server": {
"type": "stdio",
"command": "uv",
"args": ["run", "rbt-mcp-server"],
"env": {
"RBT_ROOT_DIR": "/path/to/your/document/root",
"NEO4J_URI": "bolt://localhost:7687",
"NEO4J_USER": "neo4j",
"NEO4J_PASSWORD": "your-password",
"OPENAI_API_KEY": "your-openai-api-key"
}
}
}
}2. Set Environment Variables (Optional - if not using Claude Desktop)
# Required for add_document tool
export RBT_ROOT_DIR=/path/to/your/document/root
# Required for Graphiti integration
export NEO4J_URI=bolt://localhost:7687
export NEO4J_USER=neo4j
export NEO4J_PASSWORD=your-password
export OPENAI_API_KEY=your-openai-api-key3. Test the Server
rbt-mcp-server📚 Available MCP Tools
Document Management
add_document - Sync documents to knowledge graph with automatic chunking
Supports Markdown (chunked by H3 headings) and RBT documents
Incremental sync: only updates changed chunks
Knowledge Graph Query
search_memory_nodes - Search knowledge graph nodes (entities, preferences, procedures)
search_memory_facts - Search knowledge graph facts (relationships)
get_episodes - Retrieve recent memory episodes
Data Management
delete_episode - Delete specific episode
get_entity_edge - Get entity relationship edge by UUID
delete_entity_edge - Delete entity relationship edge
clear_graph - Clear all data from knowledge graph (⚠️ irreversible)
🔗 Graphiti Integration Usage
Adding Documents to Knowledge Graph
General Markdown Documents:
add_document(
new_file_path="/absolute/path/to/document.md",
project_id="my-project",
file_path="docs/guide.md" # relative path for general docs
)RBT Documents (REQ/BP/TASK):
add_document(
new_file_path="/absolute/path/to/TASK-001.md",
project_id="knowledge-smith",
feature_id="my-feature",
rbt_type="TASK",
file_path="001" # task number for TASK documents
)Searching Knowledge
# Search for nodes (entities, preferences, procedures)
results = await search_nodes(
query="documentation preferences",
group_ids=["knowledge-smith"],
entity="Preference",
max_nodes=10
)
# Search for facts (relationships)
facts = await search_facts(
query="task dependencies",
group_ids=["knowledge-smith"],
max_facts=10
)Difference from graphiti-memory MCP
This MCP server extends the original graphiti-memory MCP with document chunking capabilities:
Original graphiti-memory: Stores entire documents as single episodes
This MCP (graphiti-chunk-mcp): Automatically chunks documents into semantic sections
RBT documents: Split by section (sec-*)
Markdown documents: Split by H3 headings (###)
Incremental updates: Only sync changed chunks
API Compatibility: All search_nodes, search_facts, get_episodes functions maintain the same interface as graphiti-memory.
📖 Documentation
Markdown Writing Guide - How to write Markdown documents that work well with the chunker
MCP Installation Guide - Detailed installation and usage instructions
🧪 Development
Install development dependencies:
uv sync --devRun tests:
RBT_ROOT_DIR=/test/root uv run pytest -vTest coverage:
RBT_ROOT_DIR=/test/root uv run pytest --cov=rbt_mcp_server --cov-report=html📝 License
MIT License
🤝 Contributing
Contributions welcome! Please open an issue or submit a pull request.
Maintenance
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