pdf-knowledge-mcp

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ingest_document

Ingest documents into a local RAG knowledge base for semantic search and Q&A. Supports text, Markdown, JSON, HTML files or raw content, chunked and vectorized with configurable parameters.

Instructions

Ingest a PDF development experience document into the local RAG knowledge base. The server chunks, vectorizes, indexes, and persists the content locally.

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": "ingest_document"
  }
}

Input Schema

Name	Required	Description
`tags`	No	Optional tags for classifying or filtering knowledge, such as parsing, rendering, font, ocr, pdfa, signature.
`title`	No	Human readable title. Defaults to the file name or source.
`source`	No	Stable source identifier, such as a file path, URL, note id, or repository path.
`content`	No	Raw text or Markdown content to ingest. Use this or filePath.
`filePath`	No	Path to a UTF-8 text, Markdown, JSON, or HTML document. Relative paths are resolved from the MCP server process cwd.
`chunkSize`	No	Approximate maximum characters per chunk.
`chunkOverlap`	No	Approximate overlapping characters between adjacent chunks.
`replaceExisting`	No	Replace existing documents with the same source before ingesting.

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Jun 25, 2026

TDQS

A4/5.0

Behavior4/5

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

With no annotations, the description clearly discloses the tool's behavior: 'The server chunks, vectorizes, indexes, and persists the content locally.' It accurately describes the write operation, though it could further address idempotency or failure modes.

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 two sentences, front-loaded with verb and resource, and contains no filler. Every sentence adds value.

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

Completeness4/5

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

Given the tool's complexity (8 parameters, no output schema), the description covers the core process but omits details about supported file types (schema allows non-PDF formats) and post-ingestion querying. It is mostly complete but has a minor inconsistency between description ('PDF') and schema (other formats).

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 coverage is 100% with parameter descriptions present. The description does not add per-parameter meaning beyond the schema, which is acceptable. Baseline score of 3 is appropriate.

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?

The description clearly states the tool's purpose: 'Ingest a PDF development experience document into the local RAG knowledge base.' It specifies the verb (ingest), resource (PDF document), and destination (RAG knowledge base), and distinguishes from sibling tools like ask_pdf_expert (query) and search_knowledge (search).

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

Usage Guidelines3/5

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

The description implies usage for adding documents to the knowledge base but does not explicitly state when to use this tool versus alternatives like ask_pdf_expert or search_knowledge. No when-not or direct comparisons are provided.

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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