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Glama

Biosamples

by io.github.pipeworx-io

Search Samples

search_samples
Read-onlyIdempotent

Search EBI BioSamples — metadata for biological samples (cell lines, tissues, organisms) referenced across EBI archives. Free-text search by organism, tissue, or keyword; returns matching samples with accession, name, organism, and release date. Keyless.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNoZero-based page number (default 0).
limitNoMax results to return (default 15, max 100).
queryYesFree-text query — organism, tissue, cell type, or any keyword (e.g. "liver", "Homo sapiens", "cancer cell line").

Schema Changelog

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

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "query": "liver"
+  },
+  {
+    "limit": 25,
+    "page": 0,
+    "query": "Homo sapiens cancer cell line"
+  }
+]
  2. First observed

TDQS

A4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering safety. The description adds that it returns specific fields (accession, name, organism, release date), but does not detail additional behaviors like rate limits or pagination limits beyond the schema.

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 two efficient sentences, front-loaded with the core purpose. Every sentence adds value with no redundancy.

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?

With 100% schema coverage, rich annotations, and no output schema needed, the description covers the tool's functionality well. It could mention pagination behavior beyond defaults, but it's not essential.

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 coverage is 100% with clear parameter descriptions. The description reinforces that query is a free-text search but adds no new parameter-level details. Baseline for full coverage is 3.

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 'Search EBI BioSamples' and specifies the type of metadata and search fields (organism, tissue, keyword). It distinguishes from siblings like 'get_sample' which retrieves a single sample.

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 mentions 'Free-text search' and 'Keyless', giving usage context. However, it does not explicitly state when not to use this tool or point to alternatives like 'get_sample' for specific sample retrieval.

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

All Biosamples toolsInspect
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TDQS

A3.8/5.0
Disambiguation2/5

Multiple tools have unclear boundaries: ask_pipeworx_beta is explicitly identical to ask_pipeworx right now, and ask_pipeworx_grounded is a subtle behavioral variant, creating a real selection hazard. The six polymarket_* tools also blur together (edges vs arbitrage vs fill_risk vs kalshi_spread all relate to finding and acting on mispricings), and scan_competitor_ai_presence is largely a wrapper over ai_visibility_check.

Naming Consistency3/5

All names are snake_case and several families share clear prefixes (ask_pipeworx, polymarket_*, pipeworx_*, scan_*), which keeps the set readable. However, the set mixes verb-first names (get_sample, compare_entities, resolve_entity) with noun-first names (entity_profile, bet_research, recent_changes, polymarket_edges), and the _beta suffix signals a status while _grounded signals a behavior, so the pattern is not predictable.

Tool Count2/5

33 tools is above the threshold where a tool set starts to feel bloated, and for a server named 'Biosamples' it is an extreme scope mismatch: 31 of 33 tools relate to Pipeworx data routing, prediction markets, memory, or subscriptions rather than biological samples. The count is also padded with near-duplicates such as ask_pipeworx_beta and scan_competitor_ai_presence.

Completeness2/5

Against the server's stated identity, the BioSamples surface is severely thin: only search_samples and get_sample exist, with no batch retrieval, project/group navigation, sample-group hierarchy, or submission/update path. The 31 unrelated tools do not fill this gap — they serve a completely different domain, so an agent using this server for biological sample data will hit dead ends.

Resources