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renezander030/graphiti-local

renezander030/graphiti-local

local-first temporal knowledge graph
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Config template (adjust for your client)
claude mcp add graphiti-local -- npx -y graphiti-local
A pasteable skeleton generated from the repository name. Check the project README for the exact package and arguments.
Star count
5 ★ · renezander030/graphiti-local · read from the GitHub search API · (checked 2026-10-16 20:00:20)
Source
collected from the punkpeye/awesome-mcp-servers list · type: MCP server
Harvest history
first seen 2026-10-15 · last seen 2026-10-16 · seen 2× · listed by 2 sources
Score
score 203 · 5 ★ · 2 sources · mcp
FAQ (answers come from our records)
How do I install it?
We did not find an install command for this repository (our install coverage is only about 4%). Check its README or releases page.
Who is it for?
We filed it under these tags: MCP 服务. The tags come from the entry itself, not a taxonomy we imposed.
Who maintains it?
repository renezander030/graphiti-local;first catalogued 2026-10-15;last seen 2026-10-16。There is no official certification or quality rating here — we record sources and dates only.
Third-party quality signals

Graphiti Local

以下摘录自该仓库的 README(片段) · 在 GitHub 读完整 README →

**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.
*Captured output excerpts with pauses condensed. Measured results and limitations.*
Try it in one command
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.
Try it locally
Install uv and
Ollama, then start Ollama. Setup downloads
need internet access. Run these commands in bash or zsh:
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.
Multiple users on Ladybug
Give each user a group, and each group its own Ladybug file:
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
Source
awesome · https://github.com/renezander030/graphiti-local
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