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Local-first MCP server that indexes a codebase into SQLite once and then lets AI agents search it instantly — offline, private, and with zero dependencies via literal substring search, incremental indexing, per-language stats, and root listing.

Local-first MCP server that indexes a codebase into SQLite once and then lets AI agents search it instantly — offline, private, and with zero dependencies via literal substring search, incremental indexing, per-language stats, and root listing.

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Python
Local

index

Index a directory into SQLite for offline, private search. Incremental indexing re-reads only changed files, enabling efficient subsequent searches.

Instructions

Index a directory so it can be searched later. Incremental: only changed files are re-read.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "root": "<root>"
    },
    "name": "index"
  }
}

Input Schema

NameRequiredDescriptionDefault
rootYesDirectory to index
no_ignoreNoDisable .gitignore/.locidxignore
extra_ignoresNoExtra ignore globs

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.1/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description carries full burden. The incremental note ('only changed files are re-read') is a useful behavioral disclosure. However, it doesn't describe side effects or prerequisites, which keeps it at a minimum viable level.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two concise sentences, no filler, information-dense.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple indexing tool with well-documented parameters, the description provides essential purpose and a behavioral caveat. No output schema is present, so the outcome is implied by 'searched later', which suffices.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so baseline of 3. Description adds no extra parameter details, just restates the primary action.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Clear verb 'Index' with resource 'a directory' and outcome 'so it can be searched later'. Distinguishes from sibling tools 'search', 'stats', 'roots' by the action.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The phrase 'so it can be searched later' implies a preparatory use case. Does not explicitly name alternatives or exclusions, but the purpose alone differentiates it from search.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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