search-mesh
SIMD-accelerated, single-pass codebase intelligence fabric for AI agents. Offload multi-keyword scans and AST context-pruning to native silicon.
Install / Use
claude mcp add jamestkelly -- npx -y github:jamestkelly/search-meshIf 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 search-mesh
search-mesh scores 78/100 on our quality scale, 2266th of 3,478 Development & Engineering skills we index.
Its MCP Server is 5.7 KB long, well organised into 14 sections with 8 code examples: a solid amount of guidance for an agent.
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 3 months ago, so search-mesh is actively maintained.
- 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 92/100, with 1 caution 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.
search-mesh compared with similar skills
All 4 of these similar skills score higher than search-mesh; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| search-mesh (this skill)by jamestkelly | 78 | 3 | 3mo ago | MCP Server |
| Agent-Reachby Panniantong | 100 | 86.1k | 13d ago | CLAUDE.md |
| headroomby headroomlabs-ai | 100 | 74.1k | today | CLAUDE.md |
| rufloby ruvnet | 100 | 73.5k | today | CLAUDE.md |
| CowAgentby zhayujie | 100 | 47.2k | today | CLAUDE.md |
Frequently asked questions
- How do I install search-mesh?
- Run
claude mcp add jamestkelly -- npx -y github:jamestkelly/search-mesh. The install tabs above show the steps for each supported agent. - Which AI agents does search-mesh 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 search-mesh safe to use?
- It is MIT-licensed and scores 92/100 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 search-mesh still maintained?
- The repository was last updated about 3 months ago, so search-mesh is actively maintained.
Skill content
View source on GitHubSearch-Mesh
Search-Mesh is a Rust-native codebase intelligence service for autonomous coding agents.
The goal is to reduce agent latency and token waste by moving repository search, syntax-aware filtering, context extraction, and precise patching into a local MCP-compatible process.
Status
This repository is in early setup. The current focus is a small, correct MVP:
- A Rust workspace with separate core and MCP crates.
- A JSON-RPC over stdio server implementing the MCP
initializelifecycle handshake, suitable for Claude Code, OpenCode, and other MCP-compatible agents. - A first search tool,
scan, backed by multi-keyword scanning. - A syntax probe tool,
ast_probe, backed by tree-sitter for Rust, Python, JavaScript, and TypeScript. - A context extraction tool,
squeeze, that returns AST-bounded source blocks. - A patch tool,
patch, that applies precise line/column edits and reports syntax validity.
SIMD acceleration, tree-sitter verification, semantic squeezing, and atomic patching are planned phases, not current guarantees.
Intended Tools
scan: scan target directories for multiple keywords in one pass.ast_probe: validate raw hits against syntax tree node types.squeeze: return the smallest useful AST-bounded code block around a hit.patch: apply byte-offset edits and verify syntax after mutation.
See docs/usage.md for local examples and docs/mcp-protocol.md for the draft protocol.
Install
Claude Code Plugin (Recommended)
This repository is a self-hosted Claude Code plugin marketplace. It bundles the search-mesh MCP server registration and the agent skill together, so /plugin install wires up both in one step:
/plugin marketplace add jamestkelly/search-mesh
/plugin install search-mesh@search-mesh
On macOS and Linux, the plugin downloads and verifies the correct prebuilt search-mesh-mcp binary automatically the first time it's used — no separate install step. Windows isn't supported by the automatic installer yet; use cargo install search-mesh-mcp or a manual binary install there.
Manual Install
For OpenCode, or Claude Code configured manually rather than through the plugin, search-mesh-mcp needs to be on your PATH first.
search-mesh-mcp is published to crates.io and as prebuilt GitHub Release binaries.
Via cargo:
cargo install search-mesh-mcp
Via prebuilt binary: download search-mesh-mcp-<target>.tar.gz for your platform (macOS arm64, macOS x64, or Linux x64) from the Releases page, extract it, and put search-mesh-mcp on your PATH.
Configure Claude Code Manually
Add to .mcp.json at your project root:
{
"mcpServers": {
"search-mesh": {
"command": "search-mesh-mcp",
"args": []
}
}
}
Configure OpenCode
Add to opencode.jsonc:
{
"mcp": {
"search-mesh": {
"type": "local",
"command": ["search-mesh-mcp"],
"enabled": true
}
}
}
Agent Skill
The Claude Code plugin install above already includes this skill. To install it manually for other agents/setups, skills/search-mesh/SKILL.md teaches an agent when to prefer scan, ast_probe, squeeze, and patch over shell tools like grep, cat, and sed. Copy it into your own skills directory:
mkdir -p ~/.claude/skills/search-mesh
cp skills/search-mesh/SKILL.md ~/.claude/skills/search-mesh/SKILL.md
Repository Layout
.claude-plugin/
plugin.json Claude Code plugin manifest.
marketplace.json Self-hosted marketplace catalog listing this plugin.
.mcp.json Bundled MCP server registration (used by the plugin).
crates/
search-mesh-core/ Core search, parsing, squeezing, and patching logic.
search-mesh-mcp/ JSON-RPC/MCP stdio server.
docs/
architecture.md System shape and phased design.
mcp-protocol.md Tool schemas and response shapes.
roadmap.md Near-term implementation plan.
usage.md Local MCP usage examples.
examples/
scan-request.jsonl Example newline-delimited JSON-RPC requests.
initialize-request.jsonl
ast-probe-request.jsonl
squeeze-request.jsonl
patch-request.jsonl
patch-target.txt
scripts/
search-mesh-mcp-launcher.sh Installs search-mesh-mcp on first use (macOS/Linux), then execs it.
skills/
search-mesh/SKILL.md Agent skill teaching when to use these tools.
Development
Install Rust with rustup, then run:
just check
Equivalent commands:
cargo fmt --all -- --check
cargo clippy --workspace --all-targets -- -D warnings
cargo test --workspace
CI And Releases
Pull requests and pushes to main run the Review workflow:
cargo fmt --all -- --checkcargo clippy --workspace --all-targets -- -D warningscargo test --workspace- MCP JSONL example smoke tests
Releases are prepared with release-plz from Conventional Commits:
release-plzopens a release PR that bumpsCargo.toml/Cargo.lockversions and updates the changelog.- Merging that PR to
maincreates a git tag and GitHub Release per changed package, and publishes both crates to crates.io. - When a
search-mesh-mcp-v*release is published, theRelease Binariesworkflow builds and attachessearch-mesh-mcpbinaries (plus a.sha256checksum file for each) for macOS (arm64, x64) and Linux (x64) as release assets.
Design Principles
- Prefer the smallest correct implementation before optimization.
- Keep protocol handling separate from core repository intelligence.
- Measure performance before adding specialized acceleration paths.
- Avoid
.unwrap()and.expect()outside tests. - Return agent-friendly payloads instead of whole files when possible.
License
MIT. See LICENSE.
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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.
