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Glama

SaSame MCP Observatory + Gold Rush Town

by online.sasame

pubmed_evidence

Read-only

PubMed citation retrieval. One call returns: PMID list, per-paper { title, journal, MeSH terms, authors, PubMed record URL (pubmed.ncbi.nlm.nih.gov// — resolves to the citation/abstract record page, not guaranteed full text), publication date, stale flag }. Abstract full text is NOT returned inline; see abstract_note for where to fetch it. Structured JSON, no free-text upsell in result. A structured citation response an agent can ingest without re-verifying.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nNoNumber of papers to return (default 5, max 10)
topicYesBiomedical topic, condition, drug, or question
intent_tokenNoFresh single-use token returned by register_intent; required for this gated tool.
freshness_daysNoFlag papers older than N days as stale

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
  2. Changed1 schema field changed
    • addedInput schema / properties / intent_token
      Added value: +{
+  "description": "Fresh single-use token returned by register_intent; required for this gated tool.",
+  "type": "string"
+}
  3. Changed1 schema field changed
    • removedInput schema / properties / intent_token
      Removed value: -{
-  "description": "One-time token from register_intent",
-  "type": "string"
-}
  4. Added

TDQS

A4.3/5.0
Behavior5/5

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

Annotations include readOnlyHint=true and openWorldHint=true, which the description matches by stating it returns structured JSON and does not return abstract full text. It adds details about stale flag and URL construction, but these align with annotations. No contradiction.

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

Conciseness4/5

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

The description is 4 sentences and front-loaded with the core purpose. It is concise but could be more structured (e.g., bullet points for output fields). Clear and efficient overall.

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 explains the return value well, lists the output fields, and notes the missing abstract. Without output schema, it compensates adequately. Could mention error handling or empty results but is sufficient for typical use.

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 description coverage is 100%, so baseline is 3. The description does not add extra meaning beyond the schema's parameter descriptions; it focuses on output fields instead.

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 'PubMed citation retrieval' and enumerates specific returned fields (PMIDs, title, journal, MeSH terms, etc.), distinguishing it from siblings like 'pubmed_lookup'. The verb is specific and the resource is well-defined.

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 implies use for structured citation retrieval, notes that abstract full text is not included, and references 'abstract_note' for further steps. However, it does not explicitly compare to 'pubmed_lookup' or specify when not to use.

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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TDQS

B3.1/5.0
Disambiguation2/5

With 94 tools spanning overlapping concepts (multiple readiness/audit/grade tools, many status checkers, deprecated aliases like trust_* vs observation_*), agents will frequently struggle to pick the right one. While each tool is individually distinct, the sheer volume and conceptual overlap (e.g., audit_mcp, readiness_report, verify_mcp_ready, lookup_readiness, recommend_mcp, subscribe_grade_changes) create high misselection risk.

Naming Consistency3/5

Most tools use snake_case with underscores, but the pattern is inconsistent: some are verb-first (audit_mcp, verify_mcp_ready, claim_start, check_engagement) while others are noun-first (receipt_issue, meter_open, work_order_open, agent_invoice_status). Deprecated aliases like trust_compare vs observation_compare further break consistency, though the majority remain readable.

Tool Count1/5

94 tools is far beyond any reasonable scope for a single server, even one with broad ambitions like 'observatory + town'. The calibration notes 50+ as extreme mismatch; this server far exceeds that. Many tools are highly specific (e.g., factory_resolve_dead_letter, visit_touch_status, start_here) and could be consolidated or split into separate servers.

Completeness3/5

The server covers a wide range of domains (auditing, claiming, receipts, meters, escrow, work orders, gold rush, town, analytics) and offers many CRUD-like operations, but several lifecycle gaps exist: no cancel/close for work orders (only open/accept/deliver/accept_delivery), escrow (only open/attest/status), or meters (only open/charge/status). Given the massive scope, important operations are missing, though core workflows are present.

Resources