Power your agent
Perintah milik penerbit sendiri. Bukan endpoint PlugMCP.
Host a copy with our keys and logs.
uvx graphiti-local==0.11.0Claude Code tidak punya tautan instal untuk perintah lokal. Salin perintah di bawah dan jalankan di terminal.
claude mcp add io.github.renezander030-graphiti-local -- uvx graphiti-local==0.11.0Jalankan di terminal.
{ "mcpServers": { "io.github.renezander030-graphiti-local": { "command": "uvx", "args": [ "graphiti-local==0.11.0" ] } }}claude_desktop_config.json
URL remote atau perintah di mesin Anda? Perbedaan kedua cara instal
Jalankan di PlugMCP
A new server you create. It is not this listing's official endpoint. Use the publisher install when you want their URL and their credentials.
BukaDari penerbit
Local memory for your agents. You approve what they learn.
Retrieve project decisions through six read-only MCP tools or the kg CLI.
Proposed updates stay in a separate queue until a human approves and applies them.
Ollama handles local inference; embedded LadybugDB stores the graph. No Docker or
cloud API key is needed for the local setup.
Local-first temporal knowledge graph with six read-only MCP tools and human-reviewed writes.
Captured output excerpts with pauses condensed. Measured results and limitations.
uvx --from git+https://github.com/renezander030/graphiti-local kg-demo
Answers a question against a small synthetic graph shipped with the package. No Ollama, no model downloads, no database setup: retrieval runs on keywords alone, so nothing contacts a model. Ask your own question by passing it as an argument.
This is the read path only. Building a graph from your own text needs extraction, which needs a model, and that is the full setup below.
Install uv and Ollama, then start Ollama. Setup downloads need internet access. Run these commands in bash or zsh:
git clone https://github.com/renezander030/graphiti-local.git
cd graphiti-local
uv sync --frozen
ollama pull qwen2.5:7b
ollama pull nomic-embed-text
export GRAPHITI_LOCAL_CONFIG="$PWD/config/ollama.example.yaml"
export KG_WORKSPACE_DIR="$PWD/workspace/local-demo"
export KG_LADYBUG_PATH="$KG_WORKSPACE_DIR/graph.ladybug"
uv run --frozen kg-ladybug-setup --database "$KG_LADYBUG_PATH" --apply
uv run --frozen kg doctor
uv run --frozen kg-ingest examples/local_memory_demo.jsonl --apply
uv run --frozen kg ask "Which database does Aurora Analytics use?" example
The synthetic example returns DuckDB. Follow the complete walkthrough to propose PostgreSQL, review and apply that update, and retrieve it from an MCP client. Model extraction can be wrong; inspect the returned facts and validity timestamps.
To review extraction before it touches the configured graph, run
kg-ingest INPUT --review-output review.jsonl, inspect the snapshot, and mark every
fact in the generated review.jsonl.review.jsonl file as accept, refuse, or
contested. The printed restore command refuses unresolved decisions and promotes a
checksum-sealed snapshot containing accepted facts only. Searches return current facts
by default; kg ask --history is the explicit historical view.
kg-ingest also accepts a Markdown/text file or a directory tree directly. Large
documents split at stable text boundaries. Transient writes retry with one stable
episode id; ingest-receipts.jsonl and ingest-failures.jsonl in the workspace show
exactly what landed and what still needs attention.
Give each user a group, and each group its own Ladybug file:
graph:
groups: [alice, bob]
database:
provider: ladybug
ladybug:
layout: per-group # default: single, one file for every group
directory: ./workspace/groups
server:
transport: streamable-http
auth:
tokens:
- {name: alice, token: "${ALICE_TOKEN}", groups: [alice]}
- {name: bob, token: "${BOB_TOKEN}", groups: [bob]}
Each file is named by the SHA-256 of its group, so no group id can point outside the
directory. Reads, kg ask and the drain open only the file of the group they address;
a token granted alice never opens Bob's file. A read names one group, or the token's
single group is used. For a tenant boundary inside one database server, use FalkorDB
or Neo4j.
Use it for local agent memory with explicit human review. Skip it if you need agents to write through MCP or want a hosted service without local setup. FalkorDB and Neo4j are also supported.
If this helps your workflow, star the repository and share your setup result.
Maintained by René Zander, who builds context layers for AI agents on temporal knowledge graphs.
Independent community project built on Graphiti, not affiliated with or endorsed by Zep. Apache-2.0.
Local-first temporal knowledge graph with six read-only MCP tools and human-reviewed writes.
{ "mcpServers": { "io.github.renezander030-graphiti-local": { "command": "uvx", "args": [ "graphiti-local==0.11.0" ] } }}Tool
Belum ada daftar tool. Server remote mendapatkannya setelah pemeriksaan kesehatan pertama.
FAQ
Salin konfigurasi stdio untuk Cursor, Claude Desktop, Claude Code, atau VS Code di halaman ini. Konfigurasi ini memakai instalasi dari penerbit, bukan proxy PlugMCP.
Tidak ada variabel lingkungan wajib yang tercantum di catatan ini.
Graphiti Local berjalan secara lokal melalui stdio.
Terakhir diperiksa 2026-11-14. Local-first temporal knowledge graph with six read-only MCP tools and human-reviewed writes.