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read_doc_contents

Extract text content from documents stored in the Document MCP Server by providing the document ID, returning the content as a readable string.

Instructions

Read the contents of a document and return it as a string.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
doc_idYesId of the document to read

Implementation Reference

  • The handler function 'read_document' implements the 'read_doc_contents' tool logic. It takes a doc_id parameter, validates that the document exists in the docs dictionary, and returns the document contents or raises a ValueError if not found.
    def read_document(
        doc_id: str = Field(description="Id of the document to read")
    ):
        if doc_id not in docs:
            raise ValueError(f"Doc with id {doc_id} not found")
        
        return docs[doc_id]
  • mcp_server.py:16-19 (registration)
    The @mcp.tool decorator registers the 'read_doc_contents' tool with the MCP server. It defines the tool name and description that appears in the tool registry.
    @mcp.tool(
        name="read_doc_contents",
        description="Read the contents of a document and return it as a string."
    )
  • The 'docs' dictionary defines the data schema and available documents that the read_doc_contents tool operates on. It maps document IDs to their content strings.
    docs = {
        "deposition.md": "This deposition covers the testimony of Angela Smith, P.E.",
        "report.pdf": "The report details the state of a 20m condenser tower.",
        "financials.docx": "These financials outline the project's budget and expenditures",
        "outlook.pdf": "This document presents the projected future performance of the system",
        "plan.md": "The plan outlines the steps for the project's implementation.",
        "spec.txt": "These specifications define the technical requirements for the equipment"
    }
  • The Field definition for the doc_id parameter specifies the input schema for the tool, describing what the parameter represents.
    doc_id: str = Field(description="Id of the document to read")
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool reads and returns content as a string, which implies a read-only operation, but doesn't disclose potential traits like authentication needs, rate limits, error handling, or whether it accesses sensitive data. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

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, efficient sentence that directly states the tool's purpose and output. It is front-loaded with the core action and has zero wasted words, making it highly concise and well-structured for quick understanding.

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?

Given the tool's low complexity (one parameter, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose but lacks details on usage guidelines, behavioral traits, or output specifics. Without annotations or an output schema, the description should do more to compensate, but it meets the minimum viable threshold for such a simple tool.

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?

The input schema has 100% description coverage, with the single parameter 'doc_id' clearly documented. The description adds no additional meaning beyond what the schema provides, such as format examples or constraints. With high schema coverage, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't need to given the schema's clarity.

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 states the action ('Read the contents') and the resource ('a document'), with a specific output format ('return it as a string'). It distinguishes from 'edit_document' by focusing on reading rather than modifying, but doesn't explicitly differentiate from 'return all the docs' which might also involve reading documents. This makes it clear but not fully sibling-differentiated.

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?

The description provides no guidance on when to use this tool versus alternatives like 'edit_document' or 'return all the docs'. It doesn't mention prerequisites, context, or exclusions. Usage is implied from the name and description alone, but no explicit guidelines are given.

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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