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Ivygrep

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Local code search and task context packs for coding agents

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β€” or use 1-click editor setup below.

Add to CursorAdd to VS Code
Manual Client & Custom JSON ConfigExpand JSON β–Ύ

Client Config & Setup

Choose your client or environment
Target File:~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "ivygrep": {
      "command": "npx",
      "args": [
        "-y",
        "ivygrep"
      ]
    }
  }
}

πŸ’‘ Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Install Directory Badge Claim listing AlternativesπŸ’» More in Developer Tools

Documentation Overview

ivygrep logo

Turn coding tasks into bounded, branch-aware context.
Search, indexing, and context generation run locally. Optional model profiles download pinned assets on first use.

CI Security Relevance Latest release MIT license

ivygrep search followed by a bounded task-context pack

Website Β· Architecture Β· Benchmarks Β· Contributing Β· Discussions

Search and build context

bash
# Find code by intent
ig "where is refresh token rotated?"

# Build context from code and current changes
ig context "fix refresh-token races" --since main --budget 8000

Abridged output:

text
# ivygrep context
Budget: 7,642 / 8,000 estimated tokens
Coverage: 7 files | 2 primary | 1 definitions | 1 dependencies | 0 dependents | 2 callers | 0 references | 1 tests | 0 config | 0 docs
Candidates: 31 retrieved | 14 selected
## Evidence
### 1. src/auth/refresh.rs:118-166 [primary, definition]
Why: task anchor; changed implementation.
Signals: lexical, symbol, git change.

Search answers where. Context answers what an agent needs to change safely.

The context command combines task anchors with commits since the branch point, staged and dirty files, issue or trace paths, and indexed relationships. It returns one bounded Markdown pack with path, lines, role, reason, and retrieval signals. --since requires a Git worktree; omit it for non-Git directories.

Install

bash
# Homebrew on macOS or Linux
brew install bvolpato/tap/ivygrep

# Release installer on macOS or Linux
curl -fsSL https://raw.githubusercontent.com/bvolpato/ivygrep/main/install.sh | sh
powershell
# WinGet on Windows
winget install --id BrunoVolpato.ivygrep --exact

# Release installer on Windows
irm https://raw.githubusercontent.com/bvolpato/ivygrep/main/install.ps1 | iex

Installers select a compatible archive, verify its SHA-256 checksum, install ig, and report the selected backend. Apple Silicon uses Metal. NVIDIA Linux hosts use the Linux x86_64 CUDA build when CUDA 13 and compute capability 8.0 or newer are available. Other systems use portable local inference. Run ig hardware to see detected hardware, compatibility limits, and the matching reinstall command.

Build from source on macOS or Linux:

bash
git clone https://github.com/bvolpato/ivygrep.git && cd ivygrep
./build.sh
mkdir -p ~/.local/bin
install -m 0755 target/release/ig ~/.local/bin/ig

Search

The first query indexes the current repository. The daemon then watches for changes and updates the index incrementally.

bash
ig "where is authentication handled?"       # hybrid semantic + lexical
ig --literal "handleAuth"                    # exact indexed lookup
ig --symbol calculate_tax                    # definitions
ig --refs calculate_tax                      # references and calls
ig --callers calculate_tax                   # caller chunks
ig "database migrations" src/api/           # path scope
ig --all "retry policy"                      # all indexed projects
ig --interactive "auth flow"                 # terminal UI
ig --web "auth flow" .                       # local Web UI

Useful controls include -n for result files, -C for context lines, --type for language, --include/--exclude path globs, --lexical-only, --hash, and --json. --hash uses lightweight local embeddings for faster startup and no model download, with lower semantic quality. Run ig --help for full reference.

On macOS laptops, background neural enhancement pauses on battery power (ig --status shows Paused: Battery Power); set IVYGREP_ENHANCE_ON_BATTERY=1 to keep it running. The lightweight hash tier keeps computing on battery so semantic results stay available.

Search notes and memories

Index notes once. Watcher keeps them current, and queries use local semantic + lexical search by default:

bash
ig --add ~/notes --wait-for-enhancement
ig -n 20 "what did we decide about cache invalidation?" ~/notes

Public MemoryQuest results: 74.9% recall@20 at 87.63 ms warm p95. Benchmark measures retrieval only; answer accuracy is outside scope.

Connect coding agents

Codex and Claude Code packages install MCP configuration plus focused task-context skill:

bash
codex plugin marketplace add bvolpato/ivygrep
codex plugin add ivygrep@ivygrep

claude plugin marketplace add bvolpato/ivygrep
claude plugin install ivygrep@ivygrep

Automatic setup detects the client, preserves existing configuration, writes the absolute ig path, verifies the MCP handshake, and runs a search:

bash
ig agent install claude
ig agent install codex
ig agent install cursor
ig agent doctor

Restart an open client after installation. Manual MCP setup is also available:

Terminal
claude mcp add -s user ig -- ig --mcp
codex mcp add ig -- ig --mcp
gemini mcp add --scope user --transport stdio ig ig --mcp

Cursor .cursor/mcp.json:

config.json
{"mcpServers":{"ig":{"type": "stdio", "command": "ig", "args": ["--mcp"]}}}

OpenCode opencode.json:

config.json
{"mcp":{"ig":{"type": "local", "command": ["ig", "--mcp"], "enabled": true}}}

Agents call ig_search for discovery. Set output=context_pack and budget_tokens=8000 when the task needs implementation context. Pass the absolute path to the active repository or worktree. Worktrees reuse the base index and store only changed chunks and tombstones.

Context packs can include definitions, callers, references, dependencies, dependents, tests, configuration, and docs.

Setup guides: Codex, Claude Code, Cursor, Gemini CLI, OpenCode, and MCP.

Recommended agent instruction:

text
Use ivygrep before broad filesystem scans. Pass absolute active worktree path.
Use natural-language queries for concepts and literal=true for identifiers.
For implementation, request output=context_pack with budget_tokens=8000.

How it works

  1. A Git-aware walker finds changed or indexable files.
  2. Tree-sitter and bounded text fallbacks produce structural chunks.
  3. SQLite stores metadata and relationships; Tantivy stores lexical postings; USearch stores hash and optional model vectors.
  4. Query routing runs bounded exact, lexical, symbol, hash, and optional neural passes before fusion.
  5. Context expands primary hits through code relationships and recent changes, then trims rendered evidence to requested token budget.

Fresh indexing publishes lexical results before vector enhancement. Worktrees reuse base index and store only divergent chunks and tombstones. Partial workspace failures return warnings with valid hits; complete failure errors.

ivygrep supports 45 language and file types. Twenty-four use Tree-sitter AST chunking: Rust, Python, Go, JavaScript, TypeScript, Java, C/C++, C#, Kotlin, Scala, PHP, Ruby, Swift, Elixir, Zig, Bash, Haskell, OCaml, Lua, Dart, Objective-C, Perl, and Starlark.

Read architecture for storage, commit order, retrieval, worktrees, protocols, security boundaries, and module ownership.

System performance

On the deterministic synthetic one-million-chunk CC0 corpus, v1.2.7 median hash-only warm CLI p95 is 6.19 ms, controlled indexing reaches 150,576 chunks/s, and the final index is 0.42 GiB across three sequential trials. This is a scale and footprint measurement, not semantic quality or agent-task performance. Hardware, repository shape, index state, and load affect absolute results.

Current-release evidence Β· Million-chunk methodology and historical paired study Β· Full benchmark dashboard

Local and private

Runtime source, queries, embeddings, results, and indexes stay local. Neural profiles download pinned model assets on first use unless cache is already populated. Use --hash, ./build.sh --hash-only, or cargo build --locked --no-default-features to avoid model downloads.

Read the full README β†’View source on GitHub β†’

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Reviews

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Frequently Asked Questions about Ivygrep

Add the following block to your claude_desktop_config.json under mcpServers: "mcpServers": { "ivygrep": { "command": "npx", "args": ["-y", "ivygrep"] } }

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Technical Specs & Signals

CategoryπŸ’»Developer Tools
More technical detailsExpand β–Ύ
TransportSTDIO
RuntimeNode.js
Last updatedSep 7, 2026
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Not scored for repo-hosted servers β€” we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership8/20
Documentation & tools10/30
Adoption & activity1/15
Community engagement0/10

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