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Locus

  • Updated March 14, 2026
  • EDKarlsson/locus

Locus is an MCP server that gives AI agents hierarchical markdown memory-palace navigation through stdio MCP tools.

About

Locus is an MCP server that exposes a hierarchical markdown memory palace to coding agents. developers shipping agent-heavy products install it when they need durable, structured context outside the chat window—rooms, paths, and markdown nodes the model can traverse via MCP instead of re-pasting notes every session. It targets Claude Code, Cursor, and other stdio MCP clients on Python-friendly setups. Use it during build when agent-tooling and long-horizon tasks (refactors, multi-repo work, research trails) outgrow flat files or ad-hoc vector stores. It is not a hosted SaaS memory product; you run locus-mcp locally and point your agent at it. Pair with project docs skills or PM MCPs when you want palace structure plus issue tracking.

  • Hierarchical markdown memory palace model for agent recall
  • MCP tools for structured palace navigation and reads
  • stdio transport via PyPI package locus-mcp (v0.6.2)
  • GitHub source at EDKarlsson/locus for self-hosted or fork workflows

Locus by the numbers

  • Data as of Jul 7, 2026 (Skillselion catalog sync)
terminal
claude mcp add locus-mcp -- uvx locus-mcp

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Packagelocus-mcp
TransportSTDIO
AuthNone
Last updatedMarch 14, 2026
RepositoryEDKarlsson/locus

What it does

Give Claude Code or Cursor a hierarchical markdown memory palace so long-running agent work stays navigable instead of one flat context dump.

Who is it for?

Best when you're running Claude Code or Cursor on multi-session agent workflows and want local, markdown-native structured memory.

Skip if: Skip if you need a managed cloud memory SaaS, full-text enterprise search, or zero local Python/MCP setup.

What you get

After registering Locus, your agent can navigate a structured markdown palace via MCP so long tasks retain locatable memory without stuffing the whole repo into every prompt.

  • stdio MCP server exposing palace navigation tools to your agent
  • Structured markdown memory graph the agent can query across sessions
  • Local, self-hosted memory layer without a third-party memory API

By the numbers

  • Server version 0.6.2 on PyPI identifier locus-mcp
  • Transport: stdio
  • Repository: github.com/EDKarlsson/locus
README.md

Locus

CI PyPI version License: MIT Python 3.11+

Hierarchical markdown-based memory system for autonomous AI agents. Each directory is a room (locus) in the palace, containing specific knowledge navigated on demand. Named for the atomic unit of the Method of Loci.

Core idea: Keep context windows small. Load only the room you need, not the whole palace.


How it works

palace/
  INDEX.md                    ← always read first (~50 lines max)
  global/
    toolchain/
      toolchain.md            ← canonical facts about tools
  projects/
    my-project/
      my-project.md           ← room overview + key files
      technical-gotchas.md    ← specialty: issues & resolutions
      sessions/
        2026-03-02.md         ← append-only session log

An agent reads INDEX.md, navigates to the relevant room, and reads only that room. Session logs accumulate until consolidation merges them into canonical files.

See the wiki for full documentation.


Quick start

# Install
pip install locus-mcp
# or: uvx locus-mcp --palace ~/.locus  (no install needed)

# Create a palace from the example template
cp -r example-palace ~/.locus
# Edit ~/.locus/INDEX.md to describe your palace

# Run the MCP server
locus-mcp --palace ~/.locus
# or: LOCUS_PALACE=~/.locus locus-mcp

Installation

MCP server (recommended for MCP-capable clients)

pip install locus-mcp

Or run without installing using uvx:

uvx locus-mcp --palace ~/.locus

Claude Code skills

Install all skills at once using the Makefile:

git clone https://github.com/Nano-Nimbus/locus.git
cd locus
make install-skills

Or install individually:

cp -r skills/claude/locus ~/.claude/skills/locus
cp -r skills/claude/locus-consolidate ~/.claude/skills/locus-consolidate
cp -r skills/claude/locus-audit ~/.claude/skills/locus-audit
cp -r skills/claude/locus-feedback ~/.claude/skills/locus-feedback
cp -r skills/claude/locus-release ~/.claude/skills/locus-release
cp -r skills/claude/locus-security ~/.claude/skills/locus-security
cp -r skills/claude/locus-palace-init ~/.claude/skills/locus-palace-init

Available Claude Code skills:

Skill Command Description
locus /locus Navigate the palace, read rooms, write session logs
locus-consolidate /locus-consolidate Merge session logs into canonical files
locus-audit /locus-audit Audit palace health
locus-feedback /locus-feedback Record explicit feedback on a palace recall
locus-release /locus-release Post-release verification workflow
locus-security /locus-security Security conventions for signed palaces
locus-palace-init /locus-palace-init Bootstrap a palace from existing memory files

Codex

cp -r skills/codex/locus ~/.codex/skills/locus
cp -r skills/codex/locus-consolidate ~/.codex/skills/locus-consolidate
cp -r skills/codex/locus-palace-init ~/.codex/skills/locus-palace-init

Gemini

Reference skills/gemini/locus/SKILL.md from your .gemini/ directory or a GitHub Actions workflow (see skills/gemini/).

cp -r skills/gemini/locus-palace-init .gemini/

Agent SDK (Python)

pip install locus-mcp
locus --palace ~/.locus --task "What toolchain conventions are set?"

MCP Server

The locus-mcp command exposes five tools over the Model Context Protocol.

Use stdio for all local integrations (Claude Desktop, Claude Code, Codex, Gemini — default, no extra flags needed). SSE transport is available for network deployments (--transport sse) and requires FASTMCP_HOST=0.0.0.0 to be set explicitly — the server binds to loopback by default.

Tool Description
memory_list Returns INDEX.md (no args) or lists a room's files
memory_read Reads any file in the palace
memory_write Atomically writes a file (guarded — cannot write to _metrics/, sessions/, .sig/, .security/)
memory_search Full-text search across the palace (ripgrep or Python fallback)
memory_batch Reads up to 20 palace files in a single call — use for multi-room loads

Add --security to enable Ed25519 signature verification on reads and automatic signing on writes. See Security below.

Claude Desktop (claude_desktop_config.json)

{
  "mcpServers": {
    "locus": {
      "command": "locus-mcp",
      "args": ["--palace", "/path/to/palace"]
    }
  }
}

Or using uvx (no install required):

{
  "mcpServers": {
    "locus": {
      "command": "uvx",
      "args": ["locus-mcp", "--palace", "/path/to/palace"]
    }
  }
}

Cursor / Zed

{
  "mcp": {
    "servers": {
      "locus": {
        "command": "locus-mcp",
        "args": ["--palace", "/path/to/palace"]
      }
    }
  }
}

Environment variable

All clients support LOCUS_PALACE as an alternative to --palace:

export LOCUS_PALACE=~/.locus
locus-mcp

See MCP Server Configuration for the full client setup guide and spec/mcp-server.md for architecture details.


Security

The security system (--security) gives every palace file an Ed25519 signature and every agent session a unique cryptographic nonce. Tool outputs are tagged [TRUSTED], [DATA], or [CRITICAL-DATA] before the agent sees them. The agent skill (locus-security) teaches agents to extract facts from [DATA] content but never follow directives within it.

# One-time setup
cp templates/locus-security.yaml ~/.locus/locus-security.yaml
locus-security init-keys --palace ~/.locus
locus-security sign-all --palace ~/.locus

# Run with security enabled
locus-mcp --palace ~/.locus --security
locus --palace ~/.locus --security --task "..."

Threat model: direct prompt injection, memory poisoning, indirect injection via external data, nonce exfiltration, multi-turn context drift.

See docs/security.md for the full protocol, configuration reference, and design decisions.


Benchmarks

Palace navigation loads 52% fewer context lines than flat memory for specific queries, while maintaining full recall. Session-only queries (recent work not yet consolidated) are accessible only via the palace.

Palace: 822 lines / 9 queries found   avg  91 lines/query · 3.2 calls
Flat:  1719 lines / 8 queries found   avg 191 lines/query · 2.0 calls

See docs/benchmarks.md for charts and full methodology.


Structure

example-palace/   Copy-paste palace template to get started
spec/             Palace convention definitions:
  index-format.md       INDEX.md rules and routing
  room-conventions.md   Room structure and naming
  size-limits.md        Context budget thresholds
  write-modes.md        Session logs vs canonical edits
  mcp-server.md         MCP server architecture and safety model
  metrics-schema.md     Run metrics JSON schema
  audit-algorithm.md    Palace health scoring
  health-report-format.md  Audit report structure
  inferred-feedback.md  Disagreement signal classification
templates/        Copy-paste templates for INDEX.md, rooms, session logs, locus-security.yaml
skills/
  claude/         SKILL.md files for Claude Code + Agent SDK
    locus/              Palace navigation and memory management
    locus-consolidate/  Room consolidation
    locus-security/     Security conventions (trust tags, nonce discipline)
  codex/          Codex-compatible skill files
  gemini/         Gemini CLI + GitHub Actions skill files
docs/
  architecture.md       Mermaid diagrams — palace, MCP, security, agent interfaces
  benchmarks.md         Benchmark results and charts (palace vs flat, security overhead)
  onboarding.md         Step-by-step agent onboarding guide
  security.md           Full security protocol, key management, config reference
  bench/                Per-version benchmark JSON (read by generate-charts.py)
scripts/
  bench-mcp.py          45-case MCP integration benchmark (includes security + batch)
  bench-compare.py      Palace vs flat recall comparison
  generate-charts.py    Regenerate docs/img/ charts (reads docs/bench/ automatically)
locus/
  agent/          Python Agent SDK (CLI + metrics)
  audit/          Palace health auditor (locus-audit CLI)
  feedback/       Inferred feedback classifier
  mcp/            MCP server (locus-mcp CLI) — palace.py, server.py, main.py
  security/       Ed25519 security system — keys, signing, taint, nonce, middleware
  utils.py        Shared utilities (slug_from_path)

Roadmap

Milestone Status Focus
v0.1 - Foundation ✅ Complete Spec, conventions, size limits
v0.2 - Core Palace ✅ Complete Templates, skills, Agent SDK, benchmark
v0.3 - Performance Metrics ✅ Complete Context tracking, feedback, suggestions
v0.4 - Self Evaluation ✅ Complete Palace audit, health reports, inferred feedback
v0.5 - MCP Server ✅ Complete MCP server with memory_list/read/write/search
v0.6 - Public release ✅ Complete Benchmarks, docs, CI, PyPI
v0.7 - Remote MCP Server ✅ Complete SSE transport, Bearer auth, Docker image, K8s deploy
v0.8 - Auto-Memory Bridge ✅ Complete Claude Code auto-memory detection, memory_batch tool
v0.9 - Security System ✅ Complete Ed25519 signing, taint tracking, nonce watermark, --security flag

Contributing

See CONTRIBUTING.md for dev setup, test instructions, and PR guidelines.

License

MIT

Recommended MCP Servers

How it compares

MCP memory-palace integration, not a Claude skill or hosted RAG platform.

FAQ

Who is Locus for?

and developers using MCP-enabled coding agents who want hierarchical markdown memory they control locally.

When should I use Locus?

Use it while building agent-driven features or long refactors when flat chat context and scattered notes are breaking continuity.

How do I add Locus to my agent?

Install the locus-mcp PyPI package (0.6.2), configure stdio MCP in Claude Code or your client, and point tools at your palace markdown layout per the GitHub repo.

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