# ministic-fishstick

> ministic-fishstick — israelflores8789-ministic-fishstick. Use this tool when you need to efficiently index and search large codebases semantically, enabling AI agents to manage and query code via high-performance vector search and indexing capabilities. It solves problems related to code discovery, reuse, and analysis, providing a minimal yet powerful MCP server solution. Ideal for use cases involving code indexing, search, and management, it accepts codebases as input and outputs searchable, indexed code representations.

Canonical page: https://skillsregistry.net/skills/israelflores8789-ministic-fishstick  
JSON: https://api.skillsregistry.net/v1/skills/israelflores8789-ministic-fishstick

## Description

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.

## Trust

- **Trust score (0–1):** 0.68
- **Verification tier:** scanned
- **Last scanned:** 2026-08-29

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** database
- **Updated:** 2026-08-29

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/bd7gdktweg)
- **Repository:** <https://github.com/israelflores8789/ministic-fishstick>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "israelflores8789-ministic-fishstick"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/israelflores8789-ministic-fishstick` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/israelflores8789-ministic-fishstick/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt