codeprysm
Graph-based code intelligence with MCP server for AI assistants. Tree-sitter parsing, semantic search, relationship analysis. Your codebase as a searchable knowledge graph.
Install / Use
claude mcp add codeprysm -- npx -y github:codeprysm/codeprysmIf the server publishes to npm under a different name, use that package instead — check the repo README.
MCP Server
Model Context Protocol server
Quality Score
Category
Development & EngineeringSupported Platforms
Our assessment of codeprysm
codeprysm scores 77/100 on our quality scale, 3688th of 4,619 Development & Engineering skills we index.
Its MCP Server is 6.0 KB long, well organised into 30 sections with 7 code examples: a thorough specification that gives an agent plenty to work with.
It has 3 GitHub stars, so there is little community track record yet; judge it on its content.
Maintenance, license and trust
- The repository was last updated about 9 months ago. That is recent enough to be usable, but agent tooling moves fast, so check the instructions against your agent's current version.
- Our last check on 2026-09-20 found the source still online.
- It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
- Its trust signals score 86/100, with 2 cautions from licensing, adoption, age or documentation. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
Safety scan
No issues foundOur scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful.
AI review by kimi-k2.7-code on 2026-09-25. Automated pattern scan on 2026-09-24. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.
codeprysm compared with similar skills
All 4 of these similar skills score higher than codeprysm; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| codeprysm (this skill)by codeprysm | 77 | 3 | 9mo ago | MCP Server |
| Agent-Reachby Panniantong | 100 | 90.5k | 19d ago | CLAUDE.md |
| headroomby headroomlabs-ai | 100 | 74.4k | today | CLAUDE.md |
| CowAgentby zhayujie | 100 | 47.2k | today | CLAUDE.md |
| ai-job-searchby MadsLorentzen | 100 | 44.9k | 1d ago | CLAUDE.md |
Frequently asked questions
- How do I install codeprysm?
- Run
claude mcp add codeprysm -- npx -y github:codeprysm/codeprysm. The install tabs above show the steps for each supported agent. - Which AI agents does codeprysm work with?
- It is written for Claude Code and Claude Desktop, as a MCP Server file. Other agents that read the same format can often use it too.
- Is codeprysm safe to use?
- Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful. It is MIT-licensed and scores 86/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is codeprysm still maintained?
- The repository was last updated about 9 months ago. That is recent enough to be usable, but agent tooling moves fast, so check the instructions against your agent's current version.
Skill content
View source on GitHubCodePrysm
A powerful tool for analyzing code repositories and generating relationship graphs using Tree-sitter abstract syntax trees. CodePrysm transforms source code into a searchable knowledge graph, enabling semantic code search, dependency analysis, and intelligent code navigation.
Overview
CodePrysm builds a comprehensive graph representation of your codebase where:
- Nodes represent code entities using three semantic types: Container (classes, interfaces, structs), Callable (functions, methods), and Data (fields, properties, constants)
- Edges represent three types of relationships: CONTAINS (hierarchy), USES (dependencies), and DEFINES (definitions)
- Embeddings enable semantic search using natural language with full metadata support
Key Features
- Semantic Code Search - Find code using natural language queries with kind/subtype filtering
- AST-Based Analysis - Precise parsing using Tree-sitter with declarative SCM tags
- Rich Dependency Graphs - Three relationship types (CONTAINS, USES, DEFINES) for comprehensive analysis
- Fine-Grained Entities - Distinguish structs from interfaces, async from sync, fields from properties
- Scalable Architecture - Handles codebases with 100K+ files
- MCP Integration - AI-powered code exploration via Model Context Protocol
- Multi-Language - Python, JavaScript/TypeScript, C/C++, C#, Go, Rust
- GPU Acceleration - Metal (macOS) and CUDA (Linux/Windows) support
Installation
From crates.io (Recommended)
cargo install codeprysm-cli
From Source
git clone https://github.com/codeprysm/codeprysm.git
cd codeprysm
cargo build --release
GPU Acceleration (Optional)
For faster embedding generation, install with GPU support:
# macOS (Apple Silicon)
cargo install codeprysm-cli --features metal
# Linux (NVIDIA GPU)
cargo install codeprysm-cli --features cuda
Prerequisites
- Docker (for Qdrant vector database)
- Rust 1.85+ (only if building from source)
Quick Start
-
Start Qdrant (required for semantic search):
docker run -d --name qdrant \ -p 6333:6333 -p 6334:6334 \ -v qdrant_storage:/qdrant/storage \ qdrant/qdrant:latest -
Initialize your codebase:
cd /path/to/your/repo codeprysm init -
Start the MCP server (optional, for AI assistants):
codeprysm mcp
How It Works
graph LR
A[Source Code] --> B[Code Graph]
B --> C[Semantic Index]
C --> D[MCP Server]
D --> E[AI Assistants]
The system operates in three main phases:
- Code Graph Generation - Parse source files into a graph structure using Tree-sitter AST
- Indexing for Search - Create embeddings for semantic search using Qdrant
- MCP Server Integration - Expose capabilities to AI assistants via MCP protocol
Documentation
- Getting Started - Setup guide
- Docker Setup - Running with Docker
- SCM Tag Convention - Query file syntax
- SCM Overlays - Adding scope metadata
CLI Commands
# Generate code graph
codeprysm init --root /path/to/repo
# Start MCP server
codeprysm mcp --root /path/to/repo --qdrant-url http://localhost:6334
# Search codebase
codeprysm search "function that handles authentication"
# Show statistics
codeprysm stats --codeprysm-dir .codeprysm
# Incremental update
codeprysm update --root /path/to/repo
Supported Languages
| Language | Containers | Callables | Data | |----------|------------|-----------|------| | Python | Classes, modules | Functions, methods, async | Fields, constants | | JavaScript/TypeScript | Classes, interfaces, enums | Functions, methods, constructors | Fields, properties | | C/C++ | Structs, classes, enums, namespaces | Functions, methods | Fields, enum constants | | C# | Classes, structs, interfaces, enums | Methods, constructors | Fields, properties | | Go | Structs, interfaces | Functions, methods | Fields | | Rust | Structs, enums, traits | Functions, methods, async | Fields, const values |
Performance & Scalability
| Codebase Size | Files | Processing Time | Memory Usage | |---------------|-------|-----------------|--------------| | Small | <1K | <1 min | <1 GB | | Medium | 1K-10K | 1-5 min | 1-4 GB | | Large | 10K-50K | 5-20 min | 4-16 GB | | Very Large | 50K-100K | 20-60 min | 16-32 GB |
Development
For development, install just command runner:
# Build
just rust-build
# Test
just rust-test
# Lint
just rust-lint
# Format
just rust-fmt
See CONTRIBUTING.md for detailed development guidelines.
Project Structure
codeprysm/
├── crates/
│ ├── codeprysm-core/ # Graph generation, tree-sitter parsing
│ ├── codeprysm-search/ # Vector search, embeddings
│ ├── codeprysm-mcp/ # MCP server
│ ├── codeprysm-cli/ # Command-line interface
│ ├── codeprysm-config/ # Configuration management
│ └── codeprysm-backend/ # Backend abstraction
├── tests/fixtures/ # Test repositories
├── docs/ # Documentation
└── docker/ # Docker configuration
Contributing
Contributions are welcome! Please see CONTRIBUTING.md for guidelines.
License
This project is licensed under the MIT License - see the LICENSE file for details.
Acknowledgments
- Tree-sitter for powerful parsing capabilities
- Qdrant for vector search
- Candle for ML inference
Related Skills
Agent-Reach
90.5kGive your AI agent eyes to see the entire internet. Read & search Twitter, Reddit, YouTube, GitHub, Bilibili, XiaoHongShu — one CLI, zero API fees.
headroom
74.4kCompress tool outputs, logs, files, and RAG chunks before they reach the LLM. 20% fewer tokens for coding agents, 60-95% fewer tokens for JSON, same answers. Library, proxy, MCP server.
CowAgent
47.2kOpen-source personal AI assistant & Agent Harness. Plans tasks, runs tools and skills, self-evolves with memory and knowledge. Multi-agent, multi-model, multi-channel. Lightweight, extensible, one-line install.
ai-job-search
44.9kThe job search that runs on your machine. AI job application framework built on Claude Code: evaluate postings, tailor CVs, write cover letters, prep interviews. Fork it and own it.
Languages
Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
