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BGPT - Scientific Paper Search

by io.github.connerlambden

Server Details

Search scientific papers with structured experimental data from full-text studies

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Status
Healthy
Last Tested
Transport
Streamable HTTP
URL
Server Listing
BGPT

Available Tools

2 tools
lookup_paperLook up paper by DOIA
Read-onlyIdempotent
Inspect

Look up a single paper by its DOI.

Args: doi: The DOI of the paper (e.g. "10.1038/s41586-024-07386-0"). output_format: "evidence" for compact claim-level evidence (default), "legacy" for original paper metadata, or "full" for both.

Returns: An envelope with found status and the paper in result, or a not-found message. A found paper counts as one result.

ParametersJSON Schema
NameRequiredDescriptionDefault
doiYes
output_formatNoevidence

Output Schema

ParametersJSON Schema
NameRequiredDescription

No output parameters

TDQS

A4.2/5.0
Behavior4/5

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

Beyond the read-only and idempotent annotations, the description adds the return envelope behavior (found status, paper in result, not-found message) and explains output_format options. It also notes that a found paper counts as one result, which is useful context.

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 well-structured with a clear purpose sentence, an Args section, and a Returns section. It is concise and information-dense without unnecessary words.

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?

For a simple lookup tool with two parameters and an output schema, the description covers the essential operational details: what it does, how to specify parameters, and what the return envelope looks like. The output schema presumably handles the paper structure, so no need to detail that here.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has no descriptions for parameters, but the description fully documents both: doi with an example, and output_format with its three possible values and default. This fully compensates for the 0% schema coverage.

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 looks up a single paper by DOI, which is a specific verb+resource. However, it does not explicitly contrast with the sibling search_papers, so it doesn't fully distinguish alternatives.

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?

Usage is implied: use this when you have a DOI for a single paper. There is no explicit guidance on when not to use it or when to prefer the sibling search_papers, so it only partially addresses alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

search_papersSearch scientific evidenceA
Read-onlyIdempotent
Inspect

Search claim-level evidence extracted from full-text scientific papers.

Args: query: Search terms (e.g. "CRISPR gene editing efficiency"). SHORT, concise queries are best. English language only. Use days_back, num_results, min_citations, and study_type instead of adding years or filters to the query. num_results: Number of results to return (1-100, default 16). First 50 results are free, then metered per result for paid users. days_back: Only return papers published within the last N days. min_citations: Only return papers with at least this many references cited. study_type: Only return papers of this study type. One of: primary study | systematic review | meta-analysis | narrative review | protocol | dataset | commentary | other. output_format: "evidence" for compact claim-level evidence (default), "legacy" for original paper metadata, or "full" for both.

Returns: An envelope whose results list contains papers with claims, experiments, exact results, demonstrated scope, limitations, and provenance.

ParametersJSON Schema
NameRequiredDescriptionDefault
queryYes
days_backNo
study_typeNo
num_resultsNo
min_citationsNo
output_formatNoevidence

Output Schema

ParametersJSON Schema
NameRequiredDescription

No output parameters

TDQS

A4.4/5.0
Behavior5/5

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

Annotations already mark the operation readOnly and idempotent, and the description adds non-obvious behavior: claim-level extraction, English-only queries, a metering/rate-limit note after 50 results, and the envelope shape with claims/experiments/provenance. No contradiction with annotations.

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 main purpose sentence is front-loaded, followed by a lean Arg/Returns structure. Every line adds usable detail, and there is no repetition of schema or annotations.

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?

For a six-parameter tool with no schema descriptions and one sibling, the description is complete: all parameters are explained, the return envelope is summarized, and annotations already cover safety. An agent can select and call this tool without further docs.

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?

With 0% schema coverage, the description does the work: it supplies defaults, ranges, allowed values for study_type and output_format, and query style guidance. The only weakness is that min_citations is defined as 'references cited', which could be confused with a paper's reference count rather than its citation count.

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 names a specific verb and resource: 'Search claim-level evidence extracted from full-text scientific papers.' This clearly differentiates by scope from a single-paper lookup, but it never explicitly references lookup_paper, so it is not fully sibling-distinctive.

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?

It provides clear operating guidance: short English queries, use days_back/num_results/min_citations/study_type instead of stuffing filters into query text, and output_format choices. This tells an agent how to invoke the tool correctly, but it does not state when to prefer lookup_paper over search_papers.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. 1 tool update
    • Changedsearch_papers2 fields changed
      • addedInput schema / properties / min_citations
        Added value: +{
+  "anyOf": [
+    {
+      "type": "integer"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null
+}
      • addedInput schema / properties / study_type
        Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null
+}
  2. 2 tool updates
    • Changedlookup_paper3 fields changed
      • removedInput schema / additionalProperties
        Removed value: -false
      • removedInput schema / properties / doi / description
        Removed value: -"The DOI of the paper (e.g. \"10.1038/s41586-024-07386-0\")."
      • addedInput schema / properties / output_format
        Added value: +{
+  "default": "evidence",
+  "type": "string"
+}
    • Changedsearch_papers5 fields changed
      • removedInput schema / additionalProperties
        Removed value: -false
      • removedInput schema / properties / days_back / description
        Removed value: -"Only return papers published within the last N days."
      • removedInput schema / properties / num_results / description
        Removed value: -"Number of results to return (1-100, default 16). First 50 results are free, then billed at $0.01/result for paid users."
      • addedInput schema / properties / output_format
        Added value: +{
+  "default": "evidence",
+  "type": "string"
+}
      • removedInput schema / properties / query / description
        Removed value: -"Search terms (e.g. \"CRISPR gene editing efficiency\") Short, concise queries are best. English language only. Don't include years or filters — use the days_back and num_results params instead."
  3. 2 tool updates
    • Changedlookup_paper2 fields changed
      • removedInput schema / properties / api_key
        Removed value: -{
-  "anyOf": [
-    {
-      "type": "string"
-    },
-    {
-      "type": "null"
-    }
-  ],
-  "default": null
-}
      • addedInput schema / properties / doi / description
        Added value: +"The DOI of the paper (e.g. \"10.1038/s41586-024-07386-0\")."
    • Changedsearch_papers4 fields changed
      • removedInput schema / properties / api_key
        Removed value: -{
-  "anyOf": [
-    {
-      "type": "string"
-    },
-    {
-      "type": "null"
-    }
-  ],
-  "default": null
-}
      • addedInput schema / properties / days_back / description
        Added value: +"Only return papers published within the last N days."
      • addedInput schema / properties / num_results / description
        Added value: +"Number of results to return (1-100, default 16). First 50 results are free, then billed at $0.01/result for paid users."
      • addedInput schema / properties / query / description
        Added value: +"Search terms (e.g. \"CRISPR gene editing efficiency\") Short, concise queries are best. English language only. Don't include years or filters — use the days_back and num_results params instead."
  4. 2 tool updates
    • First observedlookup_paper
    • First observedsearch_papers

Frequently Asked Questions

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TDQS

A4.3/5.0
Disambiguation5/5

lookup_paper and search_papers have clearly distinct purposes: one retrieves a specific paper by DOI, the other performs a query-based search. There is no overlap or ambiguity between the two tools.

Naming Consistency5/5

Both tool names follow the same verb_noun pattern: lookup_paper and search_papers. The naming is consistent, clear, and predictable, with no mixed conventions or vague verbs.

Tool Count3/5

With only 2 tools, the set feels thin for a scientific paper search service. While the two tools cover the core functions of searching and retrieving, the count is at the lower boundary of what would be considered well-scoped.

Completeness4/5

The tool surface covers the essential workflow: find papers via search and retrieve a specific paper by DOI. Minor gaps exist, such as no direct support for retrieving citations or related papers, but agents can likely accomplish primary tasks without dead ends.

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