ministic-fishstick
Minimal high-performance MCP server for semantic code indexing and vector search using Bun, SQLite, and Tree-Sitter. It enables AI agents to index, search, and manage codebases via tools like code_index_search and code_index_start.
README
ministic-fishstick
Minimal, high-performance Model Context Protocol (MCP) server for semantic code indexing and vector search powered by Bun and TypeScript.
ministic-fishstick extracts code-indexing capabilities into a standalone MCP server that can be used directly with AI CLI agents (OpenCode, Claude Desktop, Cursor) as well as GitHub Copilot Agents in VS Code.
Features
- š Bun Native & Fast: Built for Bun with zero-lock overhead and fast execution.
- š¾ Zero-Docker SQLite Vector Search: Native
bun:sqlitevector storage with Float32Array cosine similarity ā runs locally without needing Docker or external database services. - š Qdrant Support: Optional fallback or upgrade to a remote or local Qdrant vector database (
@qdrant/js-client-rest). - š³ Tree-Sitter AST Parsing: Accurate semantic code block extraction for 25+ programming languages using
web-tree-sitterandtree-sitter-wasms. - š”ļø Smart Ignore Rules (
.fishignore+.gitignore): Respects both workspace.gitignoreand.fishignorepatterns to exclude sensitive files or build output. - āļø Tiered Configuration System: Resolves configuration seamlessly across runtime MCP tool overrides, workspace
.fishstick.json, global~/.config/fishstick/fishstick.json,.envfiles, and defaults. - š¤ VS Code & Copilot Agent Ready: Includes a
vscode-extension/wrapper exposing native VS Code MCP Server contributions (contributes.mcpServers) and Copilot LM tools.
Default Behavior
When started without extra configuration:
- Embedding Provider: Defaults to OpenAI using
text-embedding-3-small(requiresOPENAI_API_KEY). - Vector Store: Defaults to local zero-docker
sqlitestorage located at<workspace>/.fishstick/vectors.sqlite. - Local Cache: Incremental file scan hashes stored in
<workspace>/.fishstick/cache.sqlite. - Target Directory: Indexes the current working directory (
process.cwd()).
Getting Started
Prerequisites
- Bun (v1.1+): Install via
curl -fsSL https://bun.sh/install | bash - An OpenAI API Key (or an alternative supported provider like Ollama, Gemini, Mistral, Bedrock, etc.)
Installation & Local Setup
# Clone the repository
git clone https://github.com/your-org/ministic-fishstick.git
cd ministic-fishstick
# Install dependencies
bun install
# Run tests
bun test
# Type-check
bun check-types
Usage
1. Running as an MCP Server (Stdio)
Start the stdio MCP server directly using Bun:
OPENAI_API_KEY="sk-..." bun run src/index.ts
2. Configuring in OpenCode / Claude Desktop / Cursor
Add ministic-fishstick to your MCP client configuration (e.g. opencode.json or claude_desktop_config.json):
{
"mcpServers": {
"fishstick": {
"command": "bun",
"args": ["run", "/path/to/ministic-fishstick/src/index.ts"],
"env": {
"OPENAI_API_KEY": "sk-...",
"VECTOR_STORE_PROVIDER": "sqlite"
}
}
}
}
3. VS Code Copilot Agent Integration
For VS Code users, the included vscode-extension/ folder provides an extension wrapper:
- Open
vscode-extension/in VS Code or install the compiled extension package. - The extension automatically registers
fishstickin VS Code's native MCP server catalog and exposes thefishstick_search_codetool to GitHub Copilot chat participants and agents.
Available MCP Tools
The server exposes five core MCP tools:
| MCP Tool Name | Description |
|---|---|
code_index_search |
Perform semantic vector search over the indexed codebase. Accepts query, optional directoryPrefix, and workspacePath. |
code_index_start |
Trigger background directory scan and file watcher (chokidar) for a workspace folder. |
code_index_status |
Retrieve current indexing state (Standby, Indexing, Indexed, Error), block counts, and file watcher progress. |
code_index_clear |
Clear vector database tables and local cache files for a workspace. |
code_index_configure |
Dynamically update embedding provider, model ID, search minScore, maxResults, or vector store at runtime. |
Configuration Hierarchy
Configuration is resolved automatically in the following order of precedence (highest to lowest):
āāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāā
ā Priority 1: Dynamic MCP Tool Calls (`code_index_config`)ā
āāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāā¤
ā Priority 2: Workspace Config (`.fishstick.json`) ā
āāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāā¤
ā Priority 3: Global User Config ā
ā (`~/.config/fishstick/fishstick.json`) ā
āāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāā¤
ā Priority 4: Environment Variables (`.env`) / Defaults ā
āāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāā
Example .fishstick.json or ~/.config/fishstick/fishstick.json
{
"enabled": true,
"vectorStore": {
"provider": "sqlite",
"qdrantUrl": "http://localhost:6333"
},
"embedder": {
"provider": "openai",
"modelId": "text-embedding-3-small",
"apiKey": "sk-..."
},
"search": {
"minScore": 0.3,
"maxResults": 20
}
}
Environment Variables (.env)
| Variable | Description | Default |
|---|---|---|
OPENAI_API_KEY |
OpenAI API Key for default embedder | ā |
VECTOR_STORE_PROVIDER |
sqlite (zero-docker local) or qdrant |
sqlite |
QDRANT_URL |
Qdrant database server URL | http://localhost:6333 |
EMBEDDER_PROVIDER |
Embedder provider (openai, ollama, gemini, etc.) |
openai |
EMBEDDER_MODEL_ID |
Model identifier | text-embedding-3-small |
SEARCH_MIN_SCORE |
Similarity score cutoff (0.0 to 1.0) | 0.3 |
SEARCH_MAX_RESULTS |
Max results returned by search | 20 |
Ignore Rules (.fishignore + .gitignore)
ministic-fishstick uses FishIgnoreController to filter files before parsing and indexing:
.gitignore: Automatically respected if present in the workspace..fishignore: Custom ignore file for indexing rules (uses standard.gitignoreglob syntax).- Auto-ignored:
.git,.fishignore,.fishstick.json,node_modules/, binary files, and vector database caches are always excluded.
License
Apache 2.0 Ā© 2026 Israel Flores-Arbolay.
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