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pubmed-search-mcp

by u9401066
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Python
Remote

read_research_chronicle

Read-onlyIdempotent

Load, list, diff, narrate, and compare stored Research Chronicles to revisit a topic's evidence across sessions without re-running searches.

Instructions

Read stored Research Chronicles: load, list, diff, narrate, analyze, compare.

This is the read facade over chronicles created by build_research_chronicle. Chronicles persist across sessions, so you can revisit a topic weeks later and see precisely what moved. Because the evidence is already stored, analysis and comparison are instant and do not re-run any search.

Actions:

  • "load": read one revision (defaults to latest) in any output format

  • "list": list stored chronicles, most recently updated first

  • "diff": compare two revisions — added, not observed/removed from the later view, and updated entries, plus evidence churn, branch churn, and the audit status transition. Absence does not prove retirement.

  • "narrate": render evidence-backed Markdown where every claim carries its entry ID and article identifiers

  • "milestones": entry-type and status distribution, per-year activity, evidence quality, and landmark entries for one chronicle

  • "compare": compare 2-5 chronicles side by side, including the evidence articles they share

The required request discriminator makes invalid field combinations unrepresentable. compare takes one typed selection containing either 2-5 topic strings or 2-5 Chronicle IDs.

Returns: Markdown or JSON text depending on the action and output format.

Examples: read_research_chronicle(request={"action":"list"}) read_research_chronicle(request={"action":"load","chronicle_id":"remimazolam-9f2b1c4d","output":"tree"}) read_research_chronicle(request={"action":"diff","chronicle_id":"remimazolam-9f2b1c4d","from_revision":1}) read_research_chronicle(request={"action":"narrate","chronicle_id":"remimazolam-9f2b1c4d","mode":"full"}) read_research_chronicle(request={"action":"milestones","chronicle_id":"remimazolam-9f2b1c4d"}) read_research_chronicle(request={"action":"compare","selection":{"kind":"topics","values":["remimazolam","propofol"]}})

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
requestYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.7.2

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already cover readOnly/idempotent/non-destructive, and the description adds genuine behavior beyond them: session-persistent evidence, instant analysis without re-search, and the important diff caveat that absence does not prove retirement. It also discloses that output is Markdown or JSON depending on action and format.

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?

Front-loaded with the action inventory, then tightly scoped bullets per action, then the request-shape note and worked examples. Every section earns its place; the examples are justified by the discriminated-union request shape.

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?

No output schema exists, and the description compensates by stating the return type (Markdown or JSON, action/format dependent) and describing what each action yields. All six actions are individually explained, so nothing needed to call the tool correctly is missing.

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?

Schema coverage is reported as 0%, but the schema itself is highly self-documenting via consts, enums and discriminators. The description still adds meaning: `load` defaults to the latest revision, `diff`/`narrate` accept revisions, `compare` takes exactly 2-5 topics or Chronicle IDs, and enumerates valid `output` formats earlier than the enum list.

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?

Opens with a specific verb and resource ("Read stored Research Chronicles") and enumerates the six actions it fronts. It explicitly frames itself as the read facade over `build_research_chronicle`, so an agent can separate it from the sibling write tool without inspecting either schema.

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?

Clear context for when this tool is the right choice: chronicles persist across sessions and analysis/comparison are instant because no search is re-run. It does not name an explicit when-not-use case or point to competing read tools, but the purpose-driven context is strong.

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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