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u9401066

pubmed-search-mcp

by u9401066
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

prepare_figure_search

Read-onlyIdempotent

Analyze scientific figures or images to extract English search terms and retrieve related biomedical literature from PubMed.

Instructions

Analyze a scientific figure or image for literature search.

═══════════════════════════════════════════════════════════════════════ 🔬 VISION-TO-LITERATURE SEARCH (Experimental) ═══════════════════════════════════════════════════════════════════════

This tool enables searching for scientific literature based on images.

WORKFLOW (the host agent performs the analysis and search): ─────────────────────────────────────────────────────────

  1. Provide an image (URL or base64-encoded)

  2. This tool returns the image using MCP ImageContent protocol

  3. YOU (the Agent) analyze the image using your vision capabilities

  4. Extract relevant ENGLISH search terms from the image

  5. Call search_biomedical_images() or unified_search() with extracted terms when literature retrieval is within the user-requested scope

  6. Return both the analysis and search results to the user

⚠️ IMPORTANT RULES: ────────────────

  • ALL search queries must be in ENGLISH (Open-i requirement)

  • This tool returns an image and guidance; it does not invoke a vision model

  • The host agent controls any subsequent search within its permissions

  • If the image shows a medical condition, extract the medical term in English

SEARCH TYPES: ─────────────

  • "comprehensive": General analysis, extract all relevant terms (default)

  • "methodology": Focus on methods, equipment, techniques shown

  • "results": Focus on data, graphs, statistical findings

  • "structure": Focus on molecular/chemical structures

  • "medical": Focus on clinical/medical imaging findings

USE CASES: ──────────

  • 📊 Scientific figures → Find papers with similar data/charts

  • 🔬 Microscopy images → Find related research

  • 🧬 Molecular structures → Find papers about the compound

  • 📈 Graphs/plots → Find papers with similar analyses

  • 🏥 Medical images → Find case reports or clinical studies

  • ⚗️ Lab equipment → Find methodology papers

IMPORTANT: ────────── Image observations are search hypotheses that require source verification. Follow the user-requested scope and the host agent's execution rules. Use English medical terminology in all search queries.

Args: source: Exactly one typed image source: {"kind": "base64", "data": "data:image/png;base64,..."} or {"kind": "url", "url": "https://example.org/figure.png"}. context: Optional context about what to look for in the image search_type: Type of analysis focus (comprehensive/methodology/results/structure/medical)

Returns: List containing: - ImageContent: The image for you to analyze - TextContent: Instructions for next steps

Example: prepare_figure_search(source={"kind": "url", "url": "https://example.com/figure1.png"}) prepare_figure_search( source={"kind": "base64", "data": "data:image/png;base64,iVBORw0..."} )

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sourceYes
contextNo
search_typeNocomprehensive

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.7.2

TDQS

A3.6/5.0
Behavior3/5

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

The description adds context about the tool's behavior (e.g., returns ImageContent, requires English terms, limitations like 'Experimental'), but it doesn't fully disclose edge cases or failure modes. The annotation readOnlyHint=true is consistent with the description, and the description adds some behavioral details beyond the annotations.

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

Conciseness3/5

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

The description is quite long and contains redundant explanations (e.g., repeating the workflow in different sections). It's structured with headings and examples, but it could be more concise. However, the structure helps readability, and the length is somewhat justified by the complexity.

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?

The description covers the tool's purpose, usage, examples, and search types, providing a fairly complete picture for an agent. It lacks some details like error handling or specific return format details, but overall it's comprehensive enough for basic usage.

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 description explains the 'source' parameter with examples and mentions 'context' and 'search_type' implicitly through the search types section. However, schema coverage is 0%, so the description carries more weight, but it doesn't fully explain all parameter nuances, especially 'context'.

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 tool's purpose: it prepares a figure or image for literature search by returning the image for analysis. It includes specific action verbs and explains the workflow, which helps distinguish it from siblings like 'search_biomedical_images' or 'unified_search'.

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 description provides detailed usage instructions, including step-by-step workflow, examples, and search types. It explicitly mentions the tool returns the image and that the host agent performs the analysis, but it doesn't explicitly differentiate when to use this tool versus alternatives like 'search_biomedical_images'.

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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