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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

stats

Get per-language file and line statistics for an indexed tree or all trees, optionally filtered by root, to quickly gauge codebase composition.

Instructions

Per-language file and line statistics for an indexed tree (or all trees).

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "stats"
  }
}

Input Schema

NameRequiredDescriptionDefault
rootNoOptional project root

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.2/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does not explicitly state that this is a safe read-only operation, nor does it describe potential side effects, performance characteristics, or required permissions.

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?

The description is a single sentence that is front-loaded with the core purpose and avoids any filler. Every word contributes value.

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

Completeness3/5

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

The description is adequate for a one-parameter tool with no output schema, but it lacks specific details about what 'file and line statistics' includes (e.g., counts, code vs. blank lines) and the return format. It is not misleading but leaves room for ambiguity.

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

Parameters4/5

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

The description adds meaningful context beyond the schema by clarifying that 'root' is optional and that omitting it applies to all trees. This supplements the schema's brief 'Optional project root' description.

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

Purpose4/5

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

The description clearly identifies the tool's purpose as providing per-language file and line statistics, with a scope of an indexed tree or all trees. It distinguishes from siblings by the unique 'statistics' resource, though it lacks an explicit action verb.

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

Usage Guidelines2/5

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

No explicit guidance is given about when to use this tool versus alternatives. The mention of 'indexed tree' implies a prerequisite that data must be indexed, but it does not elaborate on conditions or exclusions.

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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