MPM-Coding
Tool-first MCP: project-anchored AST index, symbol search, impact analysis, resumable task chains.
Ask AI about MPM-Coding
Powered by Claude ยท Grounded in docs
I know everything about MPM-Coding. Ask me about installation, configuration, usage, or troubleshooting.
0/500
Reviews
Documentation
MPM-Coding MCP
Turning AI Coding from "Demos" into "Delivery"
English | ไธญๆ
AI Coding That Survives Reality
AI coding is fun until you try it on a real repo:
- The model forgets context ("where is the code?")
- It edits based on guesses ("this should be fine")
- Long tasks drift, skip steps, or die halfway
- Later you cannot answer "what changed and why?"
MPM is not trying to make the LLM "smarter" or "better at chatting". That is the model's job.
MPM makes the work finishable: locate first (code_search), check impact (code_impact), run long tasks as a phased chain with gates (task_chain), then store the why (memo).
In AI coding, "smart" usually means "steady": solves real problems, leaves a trail, can resume, with fewer guesses and fewer misses.
Even if your git history gets messy (or you rebuild the repo), the reasoning trail can still be there: memo stores the why in .mpm-data/.
Back up .mpm-data/ and you can usually reconstruct faster (often cleaner) with AI.
What is MPM?
MPM is a set of MCP tools + rules for long-running, high-signal AI coding.
Initialize once, then paste _MPM_PROJECT_RULES.md into your client's system rules.
๐ 30-Second Start (Do This First)
1) initialize_project
2) Paste _MPM_PROJECT_RULES.md into client system rules
3) Ask directly: "Help me fix XXX and follow the rules"
If you do this first, you can start effectively without learning every tool in advance.
Core Differentiators:
| Traditional Approach | MPM Approach |
|---|---|
grep "some symbol" โ 500 results | code_search("some symbol") โ exact file:line |
| "I think this change should work" | code_impact โ full call chain analysis |
| Starting from scratch every session | system_recall โ cross-session memory |
| Long tasks drift or stop halfway | task_chain โ long-running task chain with gates |
Practical Workflow: One Complete Loop (Example)
Below is a copy-paste ready example. Paste it into any MCP client to run.
Standard Mode (Recommended for Beginners)
Read _MPM_PROJECT_RULES.md and follow it.
Task: Fix <the issue you actually have>.
Requirements:
1. Locate the code first
2. Analyze impact scope
3. Implement the fix
4. Record the change reason
The AI will automatically execute: initialize_project โ code_search โ code_impact โ modify code โ memo to record.
Strict Mode (With Explicit Gates)
Read _MPM_PROJECT_RULES.md and follow it.
Use task_chain to complete the following task:
Task: Fix <the issue you actually have>.
Phase requirements:
1. Locate phase: Use code_search to find the target function
2. Analyze phase: Use code_impact to evaluate impact scope
3. Implement phase: Fix and pass tests
4. Wrap-up phase: Use memo to record change reason
Report results after each phase and wait for confirmation before proceeding.
Closed-Loop Checklist
- Understand:
project_mapfor structure,flow_tracefor main chains - Locate:
code_searchto pinpoint symbols - Assess:
code_impactto analyze call chain impact - Change: Write code, fix compilation errors
- Verify: Run tests to confirm functionality
- Record:
memoto archive change rationale
โ ๏ธ Data Hygiene: The
.mpm-data/directory stores local data and should not be committed to version control.Project Binding:
initialize_projectcreates.mpm-data/project_config.jsonas an anchor. Future sessions auto-bind to this project root. If multiple anchors are found under a workspace aggregator folder, MPM refuses to guess and requires explicitproject_root.
What You Get
- Find the right code faster (
code_search,project_map,flow_trace) - Change with fewer surprises (
code_impact) - Run long tasks with checkpoints (
task_chain,system_hook) - Keep a usable change log (
memo,system_recall)
Quick Start
1. Build
# Windows
powershell -ExecutionPolicy Bypass -File scripts\build-windows.ps1
# Linux/macOS
./scripts/build-unix.sh
2. Configure MCP
Point to the build output: mcp-server-go/bin/mpm-go(.exe)
3. Start Using
Initialize project
Help me locate and fix <your issue>, and follow _MPM_PROJECT_RULES.md
After initialization, MPM generates _MPM_PROJECT_RULES.md automatically. Treat it as the project's operating playbook:
- It tells the LLM naming conventions, tool order, and hard constraints
- You can start effectively without learning every tool detail first
- In a new chat, ask the LLM to read this file first to reduce mistakes
Recommended first prompt: Read _MPM_PROJECT_RULES.md and follow it
4. Release Packaging (Fixed Directory)
python package_product.py
Notes:
- Output directory is fixed:
mpm-release/MyProjectManager - Each run removes previous
mpm-releasefirst, then rebuilds clean package contents
Documentation
- MANUAL.md - Complete manual (all 13 tools + best practices + case studies)
- MANUAL_ZH.md - ไธญๆ็ๅฎๆดๆๅ
- README_ZH.md - ไธญๆ็
Common Search Questions
How to do impact analysis in MCP?-> usecode_impactHow to make LLM understand business logic flow?-> useflow_traceHow to quickly understand a module/area in the system?-> useproject_map(structure) +flow_trace(main chains)How to monitor indexing progress for large repositories?-> useindex_statusHow to force full indexing?->initialize_project(force_full_index=true)
See MANUAL.md for detailed examples.
OpenCode Multi-Agent Mode
MPM provides a 5-role Agent pack (PM / Architect / Coder / Expert / Spider) for direct use in OpenCode. See opencode-agents/README.md.
Contact
- Support: GitHub Issues
- Email:
halflifezyf2680@gmail.com
License
MIT License
