
Project Knowledge Mcp
io.github.batook22Published by GitHub account batook22v1.0.6Updated Oct 24, 2026
Cross-project knowledge graph for MCP — map features across mobile, backend, and admin codebases.
Overview
Stores a cross-project knowledge graph of features so an assistant can trace how a feature flows across mobile, backend, and admin codebases.
- What you can do
- This local MCP server keeps a JSON knowledge graph of registered projects, feature workflows, and cross-project type mappings. Tools let an assistant register and scan projects, define features as ordered steps, search features, endpoints, files and screens, run reverse lookups from a file path, retrieve step context with impact analysis, suggest and check type mappings, explore directory trees, and validate that registered paths still exist. The graph is auto-saved after every mutation and can be committed to version control.
- When to use it
- Useful when one feature spans several separate codebases, such as a React Native app, a NestJS backend, and a Next.js admin panel, and the assistant needs full-stack context before editing, debugging, or testing. Less useful for a single-repository project.
- Requirements
- Node.js 18 or newer and npm 9 or newer (or pnpm/yarn); runs locally over stdio via npx or a dev dependency. An MCP-compatible client is needed. Configuration is by CLI flags such as --knowledge-file and project paths; no environment variables, API keys, or accounts are required.
Installation
In SourceWeft
- Open Project Knowledge Mcp in the dashboard and add it to a workspace.
- Enable the server for the chats that should use its tools.
Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.
Other MCP clients
Follow the launch instructions in the repository.
README
Project Knowledge MCP Server
A cross-project knowledge graph for the Model Context Protocol (MCP). Map features across mobile, backend, and admin codebases so your AI agent has full-stack context when testing, writing code, debugging, or adding features.
Quick Start
Then add to your MCP settings:
Table of Contents
- Overview
- Features
- Prerequisites
- Installation & Configuration
- Knowledge File Management
- Tools Reference
- Usage Walkthrough
- Security
- Contributing
- License
Overview
The Problem
When working on a project with multiple codebases — for example, a React Native mobile app, a NestJS backend, and a Next.js admin panel — the AI agent has no awareness of how a single feature flows across all three. This leads to incomplete context, missed dependencies, and breaking changes that could have been caught earlier.
The Solution
This MCP server stores a knowledge graph of your features, mapping each workflow step to the relevant screens, endpoints, controllers, and files in every project. The AI agent can then query this graph to understand end-to-end feature flows, detect cross-project impacts before editing files, and keep type definitions synchronized across codebases.
Features
- Multi-project awareness — register any number of projects (mobile, backend, admin, etc.)
- Feature workflow mapping — define features as ordered steps across all projects
- Auto-scanning — discover NestJS endpoints, Next.js pages, and React Native screens automatically
- Full-text search — search across features, endpoints, files, and screens
- Cross-reference lookup — given a file path, find which features reference it
- Rich context — retrieve all endpoints, screens, and files for a feature at a specific workflow step
- Breaking change detection — before editing a file, see which other projects will be affected
- Type/schema synchronization — map equivalent types across projects (e.g.,
ProductCreateDto↔ProductFormSchema) - Architecture exploration — browse any project's directory tree with keyword filtering and content highlighting
- Health validation — verify that all registered file paths still exist; auto-detect stale entries
- Persistent knowledge — auto-saves to a JSON file after every mutation; can be git-tracked and shared
- 100% dynamic — all configuration via CLI arguments and runtime tools; no source code edits required
Prerequisites
- Node.js >= 18
- npm >= 9 (or pnpm / yarn equivalent)
- An MCP-compatible client (e.g., VS Code with Cline, any AI-powered IDE)
Installation & Configuration
Install from npm (recommended)
Or run directly without installing:
Build from Source
CLI Flags
All configuration is provided via CLI arguments. No environment variables or configuration files are required.
MCP Client Configuration
Basic setup — register projects at runtime via tools:
Bootstrap setup — pre-register projects at startup:
Knowledge File Management
The knowledge file is a plain JSON file that stores all registered projects, feature workflows, and type mappings. Understanding where it lives is essential for maintaining a consistent knowledge graph.
The Shared File Pattern
If your fullstack projects live in separate directories (e.g., backend/, mobile/, admin/), each IDE window starts the MCP server from a different working directory. Without --knowledge-file, each instance creates its own fragment:
This defeats the purpose of cross-project awareness. Always use --knowledge-file with an absolute path to point all IDE windows to the same file:
Use the same --knowledge-file path in every IDE window, regardless of which sub-project you have open. All instances read and write to the same file, keeping the knowledge graph complete and consistent.
When the Default Is Safe
The default path (no --knowledge-file) is only safe when you open the monorepo root — the single directory containing all sub-projects:
If your projects are in separate repositories or directories, always use --knowledge-file.
Sharing with Your Team
Since the knowledge file is plain JSON, you can commit it to version control and share it with your team:
Guideline: One fullstack project = one knowledge file. Use
--knowledge-filewith an absolute path whenever your projects live in separate directories.
Tools Reference
Project Management
Feature Management
Search & Query
Type/Schema Synchronization
Architecture Exploration
Validation
Persistence
Usage Walkthrough
This walkthrough demonstrates the core workflow using a real multi-project setup (NestJS backend, React Native mobile, Next.js admin panel). Domain names have been anonymized — "products" instead of "stations", "orders" instead of "reports" — but every command shown was run against actual projects.
Step 1: Register Projects
Step 2: Scan Projects
Discover endpoints, screens, and pages automatically:
The scanners discover 150+ endpoints, 200+ screens, and multiple admin pages across all registered projects.
Step 3: Define a Feature
Register an auth feature — a straightforward flow that touches all three projects:
Step 4: Query Features
Compact mode — get a summary:
Returns: 5 steps, 5 test scenarios, mobile=5 screens, backend=5 endpoints, admin=1 page.
Verbose mode — get full workflow details:
Returns all 5 steps with full mobile screens, backend endpoints, controllers, and file paths.
With health check — verify all registered paths exist:
Returns: Health: 5/5 backend ok, mobile=5/5, admin=1/5, 5 test scenarios.
Step 5: Search and Cross-Reference
Search across the knowledge graph:
Returns 100+ results across features, workflow steps, backend mappings, mobile mappings, type mappings, and file contents.
Find cross-project references to a file:
Returns:
- Feature associations: Which features reference this file (steps 1–5 of the auth feature)
- Graph-registered: 5 exact matches (steps 1–5 of the auth feature, all backend), plus the admin Login page
- Scan-discovered: All files across all projects that import or reference
auth.controller.ts
Step 6: Type Mappings
Register a cross-project type mapping:
Check what references a type before changing it:
Returns all files across all projects that define or reference productId.
Auto-discover potential type mappings:
Scans all registered projects and finds exact type name matches — returns suggestions with source and target file paths ready to register.
Step 7: Validate and Export
Validate knowledge health:
Checks all registered file paths across all features and type mappings. Returns a report of existing and missing entries.
Confirm persistence:
The knowledge graph is auto-persisted after every mutation — register_project, register_feature, register_type_mappings, and validate_knowledge with fix=true all write to disk immediately. Use export_knowledge to confirm the file path before committing to version control:
Returns the path to the knowledge file. Git-track this file to share context with your team.
Security
- Knowledge file is plain JSON — you control where it is stored and who has access
- No credentials stored — this MCP only stores project paths and feature mappings
- File scanning is read-only — scanners only read files, never modify them
Contributing
Contributions are welcome. Please open an issue or pull request for any improvements, bug fixes, or feature requests.
License
Source: README.md at commit 5930c5c
Tools
0Version history
1- v1.0.6LatestSep 16, 2026
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- Reached in the last 30 days25 pts
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- Auth declared10 pts
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- Tools listed15 pts
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- DescriptionRequired15 pts
- Logo10 pts
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