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kg MCP server

by nnar1o·io.github.nnar1o/kg-mcp·v0.3.0·9 stars

Local knowledge graph memory MCP server for AI assistants.

C63/100grade C
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Safety scan
C63/100

full report

Adoption
Growing

9 stars

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If you have run it, two minutes of your experience saves the next person an afternoon.

kg tools

No tool declarations could be read from the package source. They show once the server is installed.

Public scan report

scanner v0.1.9 · 2026-09-24 · same rubric, same numbers if you re-run it

no findings
  • –Code scanremote-only server, no package to scann/a
  • –Live reliabilityno gateway calls yet and no remote to proben/a
  • –Tool poisoningtools not inspected (local package is not executed); not countedn/a
  • Auth qualityno auth information5/15
  • Maintenancelast push 49 days ago12/15
  • Maintainer identityregistry namespace matches repository owner; GitHub account older than a year8/10
Overall 63/100. Components that don't apply are left out of the denominator. Any critical finding is an F.RubricAppeal a findingJSON

How kg compares

Against every graded MCP server, from our own scans and uptime checks. Updated after each scan run.

Safety score
63/100
higher than 18% of 48,255 servers
GitHub stars
9
more than 87% of 28,688 servers

Install kg in Claude Code, Cursor or VS Code

The registry entry has no remote endpoint or installable package.

What the publisher says

From the kg repository's README, as published. We do not edit it. Read it on GitHub

kg - local knowledge graph for your AI assistants

Beta - APIs may still change and some bugs are still expected.

kg gives your AI assistant persistent, structured, editable project memory stored locally as a knowledge graph.

Instead of relying only on document chunk retrieval, you can keep architecture, decisions, incidents, rules, dependencies, and workflows in a graph that is readable, reviewable, and Git-friendly.

Use it when you want your assistant to understand an existing project across sessions — not start from zero every time.

Why use it

  • Persistent memory — keep project knowledge between conversations
  • Structured, not fuzzy — inspect nodes, edges, facts, and gaps directly
  • Editable and reviewable — store graphs as *.kg files with readable diffs
  • Local-first — your project memory stays on your machine in git-friendly format
  • Works with MCP clients — connect it as a local stdio MCP server

Why not just RAG

Classic RAG is good for retrieving text chunks from documents.

kg-mcp is better when you want:

  • stable project memory instead of repeated retrieval
  • explicit facts, relations, and dependencies
  • graph updates during real work with the assistant
  • something you can inspect, version, diff, and improve over time

Installation

From crates.io

cargo install kg-cli

From script

Recommended install:

curl -sSL https://raw.githubusercontent.com/nnar1o/kg/master/install.sh | sh

You can also download a ready binary from GitHub Releases.

Connect kg-mcp to Your AI Client

Add kg-mcp as a local stdio MCP server.

Example config:

{
  "mcpServers": {
    "kg": {
      "command": "/absolute/path/to/kg-mcp"
    }
  }
}

After that:

  1. restart your AI client,
  2. confirm the kg MCP server is available,
  3. start using the prompts below.

Full MCP setup and reference: docs/mcp.md

SCL quickstart

kg understands short, verb-first English commands (SCL — Simple Command Language). The active graph is resolved from your config automatically.

find "compressor defrost"
get concept:refrigerator
add concept:smart_fridge --name "Smart Fridge" --description "Connected refrigerator"
modify concept:smart_fridge --importance 0.9
remove concept:old_idea
connect process:compressor_control TRIGGERS process:auto_defrost
disconnect process:compressor_control TRIGGERS process:auto_defrost
list nodes
stats
use fridge
help

Core verbs

IDs

Format: :snakecase — e.g. concept:fridge, bug:doorseal, process:compressor_cycle.

Relations

HAS USES STOREDIN TRIGGERS CREATEDBY AFFECTEDBY AVAILABLEIN DOCUMENTEDIN DEPENDSON TRANSITIONS DECIDEDBY GOVERNEDBY READS_FROM

Tips

Shortened. The full README is on GitHub.

Nothing above is checked by us. What we check is on the safety report.

kg: common questions

Is kg MCP server safe?
With care: it is graded C, so read the findings first (63/100). Read the kg safety report
Does kg need an API key?
Not as far as the registry entry and our scan can tell: no credentials are declared or required.
Is kg maintained?
The last commit was 90 days ago (2026-08-05). The latest release is v0.3.0.
What can I use instead of kg?
Servers from other publishers that do the same job: Codebase Memory MCP server, Neo4j Memory MCP server and State Memory MCP server.
How does kg compare with other MCP servers?
safety score 63/100 (higher than 18% of 48,255 servers); github stars 9 (more than 87% of 28,688 servers). Full comparison.

Alternatives to kg

Same job from other publishers: the closest match first, then the best rated.

  • Codebase Memory
    Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.
    C
  • Neo4j Memory
    MCP Neo4j Knowledge Graph Memory Server
    A
  • State Memory MCP
    Persistent workflow graph server tracking tasks, decisions, spatial entities, and blockers.
    A