limps
Local Intelligent MCP Planning Server — A document and planning layer for AI assistants. No subscriptions, no cloud. Point limps at any folder (local, synced, or in git). One shared source of truth across Claude, Cursor, Codex, and any MCP-compatible tool.


Table of Contents
Quick Start
npm install -g @sudosandwich/limps
limps init my-project --docs-path ~/Documents/my-planning-docs
limps config sync-mcp --client cursor
limps config sync-mcp --client claude-code
Run this in the folder where you want to keep the docs and that's it. Your AI assistant now has access to your documents and nothing else. The folder can be anywhere—local, synced, or in a repo; limps does not require a git repository or a plans/ directory.
Features
- Document CRUD + full-text search across any folder of Markdown files
- Plan + agent workflows with status tracking and task scoring
- Next-task suggestions with score breakdowns and bias tuning
- Sandboxed document processing via
process_doc(s) helpers
- Multi-client sync for Cursor, Claude, Codex, and more
- Extensions for domain-specific tooling (e.g., limps-headless)
- Knowledge graph — Entity extraction, hybrid retrieval, conflict detection, and graph-based suggestions
- Health automation — Staleness detection, code drift checks, status inference, and auto-fix proposals
- Advanced task scoring — Dependency-aware prioritization with per-plan/agent weight overrides
- MCP Registry — Published to the official MCP Registry (
registry.modelcontextprotocol.io)
What to know before you start
- Local only — Your data stays on disk (SQLite index + your files). No cloud, no subscription.
- Restart after changes — If you change the indexed folder or config, restart the MCP server (or rely on the file watcher) so the index and tools reflect the current state.
- Sandboxed user code —
process_doc and process_docs run your JavaScript in a QuickJS sandbox with time and memory limits; no network or Node APIs.
- One optional network call —
limps version --check fetches from the npm registry to compare versions. All other commands (serve, init, list, search, create/update/delete docs, process_doc, etc.) do not contact the internet. Omit version --check if you want zero external calls.
How I Use limps
I use limps as a local planning layer across multiple AI tools, focused on create → read → update → closure for plans and tasks. The MCP server points at whatever directory I want (not necessarily a git repo), so any client reads and updates the same source of truth.
Typical flow:
- Point limps at a docs directory (any folder, local or synced).
- Use CLI + MCP tools to create plans/docs, read the current status, update tasks, and close work when done.
- Sync MCP configs so Cursor/Claude/Codex all see the same plans.
Commands and tools I use most often:
- Create:
limps init, create_plan, create_doc
- Read:
list_plans, list_agents, list_docs, search_docs, get_plan_status
- Update:
update_doc, update_task_status, manage_tags
- Close:
update_task_status (e.g., PASS), delete_doc if needed
- Analyze:
graph health, graph search, graph check, health check
Full lists are below in "CLI Commands" and "MCP Tools."
How You Can Use It
limps is designed to be generic and portable. Point it at any folder with Markdown files and use it from any MCP-compatible client. No git repo required. Not limited to planning—planning (plans, agents, task status) is one use case; the same layer gives you document CRUD, full-text search, and programmable processing on any indexed folder.
Common setups:
- Single project: One docs folder for a product.
- Multi-project: Register multiple folders and switch with
limps config use.
- Shared team folder: Put plans in a shared location and review changes like code.
- Local-first: Keep everything on disk, no hosted service required.
Key ideas:
- Any folder — You choose the path; if there’s no
plans/ subdir, the whole directory is indexed. Use generic tools (list_docs, search_docs, create_doc, update_doc, delete_doc, process_doc, process_docs) or plan-specific ones (create_plan, list_plans, list_agents, get_plan_status, update_task_status, get_next_task).
- One source of truth — MCP tools give structured access; multiple clients share the same docs.
Why limps?
The problem: Each AI assistant maintains its own context. Planning documents, task status, and decisions get fragmented across Claude, Cursor, ChatGPT, and Copilot conversations.
The solution: limps provides a standardized MCP interface that any tool can access. Your docs live in one place—a folder you choose. Use git (or any sync) if you want version control; limps is not tied to a repository.
Supported Clients
| Cursor | .cursor/mcp.json (local) | limps config sync-mcp --client cursor |
| Claude Code | .mcp.json (local) | limps config sync-mcp --client claude-code |
| Claude Desktop | Global config | limps config sync-mcp --client claude --global |
| OpenAI Codex | ~/.codex/config.toml | limps config sync-mcp --client codex --global |
| ChatGPT | Manual setup | limps config sync-mcp --client chatgpt --print |
Note: By default, sync-mcp writes to local/project configs. Use --global for user-level configs.
Installation
npm install -g @sudosandwich/limps
Project Setup
Initialize a New Project
limps init my-project --docs-path ~/Documents/my-planning-docs
This creates a config file and outputs setup instructions.
Register an Existing Directory
limps config add my-project ~/Documents/existing-docs
If the directory contains a plans/ subdirectory, limps uses it. Otherwise, it indexes the entire directory.
Multiple Projects
limps init project-a --docs-path ~/docs/project-a
limps init project-b --docs-path ~/docs/project-b
limps config use project-a
LIMPS_PROJECT=project-b limps list-plans
Client Setup
Automatic (Recommended)
limps config sync-mcp --client cursor
limps config sync-mcp --client cursor --print
limps config sync-mcp --client cursor --global
limps config sync-mcp --client cursor --path ./custom-mcp.json
Manual Setup
Cursor
Add to .cursor/mcp.json in your project:
{
"mcpServers": {
"limps": {
"command": "limps",
"args": ["serve", "--config", "/path/to/config.json"]
}
}
}
Claude Code
Add to .mcp.json in your project root:
{
"mcpServers": {
"limps": {
"command": "limps",
"args": ["serve", "--config", "/path/to/config.json"]
}
}
}
Claude Desktop
Claude Desktop runs in a sandbox—use npx instead of global binaries.
Add to ~/Library/Application Support/Claude/claude_desktop_config.json:
{
"mcpServers": {
"limps": {
"command": "npx",
"args": [
"-y",
"@sudosandwich/limps",
"serve",
"--config",
"/path/to/config.json"
]
}
}
}
Windows (npx)
On Windows, use cmd /c to run npx:
{
"mcpServers": {
"limps": {
"command": "cmd",
"args": [
"/c",
"npx",
"-y",
"@sudosandwich/limps",
"serve",
"--config",
"C:\\path\\to\\config.json"
]
}
}
}
OpenAI Codex
Add to ~/.codex/config.toml:
[mcp_servers.limps]
command = "limps"
args = ["serve", "--config", "/path/to/config.json"]
ChatGPT
ChatGPT requires a remote MCP server over HTTPS. Deploy limps behind an MCP-compatible HTTP/SSE proxy.
In ChatGPT → Settings → Connectors → Add custom connector:
- Server URL:
https://your-domain.example/mcp
- Authentication: Configure as needed
Print setup instructions:
limps config sync-mcp --client chatgpt --print
Transport
- Current: stdio (local MCP server, launched by your client).
- Remote clients: Use an MCP-compatible proxy for HTTPS clients (e.g., ChatGPT).
- Roadmap: SSE/HTTP transports are planned but not implemented yet.
CLI Commands
Viewing Plans
limps list-plans
limps list-agents <plan>
limps status <plan>
limps next-task <plan>
Project Management
limps init <name>
limps serve
limps config list
limps config use <name>
limps config show
limps config sync-mcp
Health & Automation
limps health check
limps health staleness [plan]
limps health drift [plan]
limps health inference [plan]
limps proposals list
limps proposals apply <id>
limps proposals apply-safe
Knowledge Graph
limps graph reindex
limps graph health
limps graph search <query>
limps graph trace <entity>
limps graph entity <id>
limps graph overlap
limps graph check [type]
limps graph suggest <type>
limps graph watch
Scoring & Repair
limps score-all <plan>
limps score-task <task-id>
limps repair-plans [--fix]
Configuration
Config location varies by OS:
| macOS | ~/Library/Application Support/limps/config.json |
| Linux | ~/.config/limps/config.json |
| Windows | %APPDATA%\limps\config.json |
Config Options
{
"plansPath": "~/Documents/my-plans",
"docsPaths": ["~/Documents/my-plans"],
"fileExtensions": [".md"],
"dataPath": "~/Library/Application Support/limps/data",
"extensions": ["@sudosandwich/limps-headless"],
"tools": {
"allowlist": ["list_docs", "search_docs"]
},
"scoring": {
"weights": { "dependency": 40, "priority": 30, "workload": 30 },
"biases": {}
}
}
plansPath | Directory for structured plans (NNNN-name/ with agents) |
docsPaths | Additional directories to index |
fileExtensions | File types to index (default: .md) |
dataPath | SQLite database location |
tools | Tool allowlist/denylist filtering |
extensions | Extension packages to load |
scoring | Task prioritization weights and biases |
graph | Knowledge graph settings (e.g., entity extraction options) |
retrieval | Search recipe configuration for hybrid retrieval |
Environment Variables
LIMPS_PROJECT | Select active project for CLI commands | LIMPS_PROJECT=project-b limps list-plans |
LIMPS_ALLOWED_TOOLS | Comma-separated allowlist; only these tools are registered | LIMPS_ALLOWED_TOOLS="list_docs,search_docs" |
LIMPS_DISABLED_TOOLS | Comma-separated denylist; tools to hide | LIMPS_DISABLED_TOOLS="process_doc,process_docs" |
Precedence: config.tools overrides env vars. If allowlist is set, denylist is ignored.
MCP Tools
limps exposes MCP tools for AI assistants:
| Documents | process_doc, process_docs, create_doc, update_doc, delete_doc, list_docs, search_docs, manage_tags, open_document_in_cursor |
| Plans | create_plan, list_plans, list_agents, get_plan_status |
| Tasks | get_next_task, update_task_status, configure_scoring |
| Health | check_staleness, check_drift, infer_status, get_proposals, apply_proposal |
| Knowledge Graph | graph (unified: health, search, trace, entity, overlap, reindex, check, suggest) |
Knowledge Graph
The knowledge graph builds a structured, queryable representation of your planning documents. It extracts 6 entity types (plan, agent, feature, file, tag, concept) and their relationships (ownership, dependency, modification, tagging, conceptual links). Use it to find conflicts, trace dependencies, and get graph-based suggestions.
limps graph reindex
limps graph health --json
limps graph search "auth" --json
limps graph trace plan:0042 --direction down
limps graph check --json
limps graph suggest dependency-order
See Knowledge Graph Architecture and CLI Reference for details.
Health & Automation
limps includes automated health checks that detect issues and suggest fixes:
- Staleness — Flags plans/agents not updated within configurable thresholds
- Code drift — Detects when agent frontmatter references files that no longer exist
- Status inference — Suggests status changes based on dependency completion and body content
- Proposals — Aggregates all suggestions into reviewable, apply-able fixes
limps health check --json
limps proposals apply-safe
Skills & Commands
This repo ships Claude Code slash commands in .claude/commands/ and a Vercel Skills skill in skills/limps-planning.
Claude Code commands (available automatically when limps is your working directory):
/create-feature-plan | Create a full TDD plan with agents |
/run-agent | Pick up and execute the next agent |
/close-feature-agent | Mark an agent PASS and clean up |
/update-feature-plan | Revise an existing plan |
/audit-plan | Audit a plan for completeness |
/list-feature-plans | List all plans with status |
/plan-list-agents | List agents in a plan |
/plan-check-status | Check plan progress |
/pr-create | Create a PR from the current branch |
/pr-check-and-fix | Fix CI failures and update PR |
/pr-comments | Review and respond to PR comments |
/review-branch | General code review of current branch |
/review-mcp | Review code for MCP/LLM safety |
/attack-cli-mcp | Stress-test CLI + MCP for robustness |
Vercel Skills (for other AI IDEs):
Install the limps planning skill to get AI-powered guidance for plan creation, agent workflows, and task management:
npx skills add https://github.com/sudosandwich/limps/tree/main/.claude/skills/limps-plan-operations
npx skills add sudosandwich/limps
Available Skills:
limps-plan-operations | Plan identification, artifact loading, distillation rules, and lifecycle guidance using limps MCP tools |
mcp-code-review | Security-focused code review for MCP servers and LLM safety |
branch-code-review | General code review for design, maintainability, and correctness |
git-commit-best-practices | Conventional commits and repository best practices |
See skills.yaml for the complete manifest of the .claude/skills packages installed via npx skills add above; the separate skills/limps-planning/ package in this repo is a legacy distribution and new consumers should prefer the .claude/skills method.
Extensions
Extensions add MCP tools and resources. Install from npm:
npm install -g @sudosandwich/limps-headless
Add to config:
{
"extensions": ["@sudosandwich/limps-headless"],
"limps-headless": {
"cacheDir": "~/Library/Application Support/limps-headless"
}
}
Available extensions:
@sudosandwich/limps-headless — Headless UI contract extraction, semantic analysis, and drift detection (Radix UI and Base UI migration).
Obsidian Compatibility
limps works with Obsidian vaults. Open your plans/ directory as a vault for visual editing:
- Full YAML frontmatter support
- Tag management (frontmatter and inline
#tag)
- Automatic exclusion of
.obsidian/, .git/, node_modules/

Development
git clone https://github.com/paulbreuler/limps.git
cd limps
npm install
npm run build
npm test
This is a monorepo with:
packages/limps — Core MCP server
packages/limps-headless — Headless UI extension (Radix/Base UI contract extraction and audit)
Used in Production
limps manages planning for runi, using a separate folder (in this case a git repo) for plans.
Creating a feature plan
The fastest way is the /create-feature-plan slash command (Claude Code) — it handles numbering, doc creation, and agent distillation automatically via MCP tools. See .claude/commands/create-feature-plan.md for the full spec.
You can also run the same steps manually with MCP tools:
list_plans → determine next plan number
create_plan → scaffold the plan directory
create_doc → add plan, interfaces, README, and agent files
update_task_status → track progress
Plans follow this layout:
NNNN-descriptive-name/
├── README.md
├── NNNN-descriptive-name-plan.md
├── interfaces.md
└── agents/
├── 000_agent_infrastructure.agent.md
├── 001_agent_feature-a.agent.md
└── ...
Numbered prefixes keep plans and agents lexicographically ordered. get_next_task uses the agent number (plus dependency and workload scores) to suggest what to work on next.
Deep Dive
Plan Structure
plans/
├── 0001-feature-name/
│ ├── 0001-feature-name-plan.md # Main plan with specs
│ ├── interfaces.md # Interface contracts
│ ├── README.md # Status index
│ └── agents/ # Task files
│ ├── 000-setup.md
│ ├── 001-implement.md
│ └── 002-test.md
└── 0002-another-feature/
└── ...
Agent files use frontmatter to track status:
---
status: GAP | WIP | PASS | BLOCKED
persona: coder | reviewer | pm | customer
depends_on: ["000-setup"]
files:
- src/components/Feature.tsx
---
Task Scoring Algorithm
get_next_task returns tasks scored by:
| Dependency | 40 | All dependencies satisfied = 40, else 0 |
| Priority | 30 | Based on agent number (lower = higher priority) |
| Workload | 30 | Based on file count (fewer = higher score) |
Biases adjust final scores:
{
"scoring": {
"biases": {
"plans": { "0030-urgent-feature": 20 },
"personas": { "coder": 5, "reviewer": -10 },
"statuses": { "GAP": 5, "WIP": -5 }
}
}
}
RLM (Recursive Language Model) Support
process_doc and process_docs execute JavaScript in a secure QuickJS sandbox. User-provided code is statically validated and cannot use require, import, eval, fetch, XMLHttpRequest, WebSocket, process, timers, or other host/network APIs—so it cannot make external calls or access the host.
await process_doc({
path: "plans/0001-feature/plan.md",
code: `
const features = extractFeatures(doc.content);
return features.filter(f => f.status === 'GAP');
`,
});
Available extractors:
extractSections() — Markdown headings
extractFrontmatter() — YAML frontmatter
extractFeatures() — Plan features with status
extractAgents() — Agent metadata
extractCodeBlocks() — Fenced code blocks
LLM sub-queries (opt-in):
await process_doc({
path: "plans/0001/plan.md",
code: "extractFeatures(doc.content)",
sub_query: "Summarize each feature",
allow_llm: true,
llm_policy: "force",
});
MCP Resources
Progressive disclosure via resources:
plans://index | List of all plans (minimal) |
plans://summary | Plan summaries with key info |
plans://full | Full plan documents |
decisions://log | Decision log entries |
Example: Custom Cursor Commands
Create .cursor/commands/run-agent.md:
# Run Agent
Start work on the next available task.
## Instructions
1. Use `get_next_task` to find the highest-priority task
2. Use `process_doc` to read the agent file
3. Use `update_task_status` to mark it WIP
4. Follow the agent's instructions
This integrates with limps MCP tools for seamless task management.
What is MCP?
Model Context Protocol is a standardized protocol for AI applications to connect to external systems. Originally from Anthropic (Nov 2024), now part of the Linux Foundation's Agentic AI Foundation.
License
MIT