get_summaryPDBe (Protein Data Bank in Europe, EBI): get a PDB entry summary — title, experimental method, release date, source organism, and entity counts (polypeptide/ligand/water/...). Keyless. The EBI counterpart to RCSB PDB. Pass a 4-char PDB id like "1cbs".
| Name | Required | Description | Default |
|---|---|---|---|
| pdb_id | Yes | A 4-char PDB id, e.g. "1cbs". |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {
+ "pdb_id": "1cbs"
+ },
+ {
+ "pdb_id": "2hhb"
+ }
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnly, idempotent, and non-destructive behavior. The description adds useful context: no auth needed ('keyless'), and enumerates the return fields. No contradiction; it supplements the annotations well.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise—two sentences plus a brief note—while covering purpose, input, output, and source. Every sentence adds value, and key information (purpose, fields, example) is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given one parameter, high schema coverage, and annotations, the description fully covers the tool's purpose, input, and output fields. No output schema exists, but the description lists what the summary includes, making it self-contained.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a clear description of pdb_id. The description reinforces this with an example ('1cbs'), but adds no new semantic meaning beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves a PDB entry summary with specific fields (title, experimental method, release date, source organism, entity counts) and specifies the input format (4-char PDB ID). It distinguishes itself by naming the source (EBI) and contrasting with RCSB PDB.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions the tool is the EBI counterpart to RCSB PDB and is 'keyless', implying no authentication needed, but does not provide explicit guidance on when to use this tool over alternatives or any exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Many tools overlap in purpose: ask_pipeworx, ask_pipeworx_grounded, ask_pipeworx_beta, and deep_research all perform similar data lookups with slight variations. Prediction market tools (bet_research, polymarket_arbitrage, polymarket_edges) also overlap. Only the three PDBe-specific tools are clearly distinct, but overall the set is confusing.
Tool names follow no consistent pattern: some are verb_noun (ask_pipeworx, get_molecules), others are noun_verb (ai_visibility_check), or have mixed conventions (generate_llms_txt, uniprot_mappings). The variety of verbs (ask, bet, compare, discover, generate, get, list, recall, remember) makes it hard to predict tool names.
With 34 tools, the server is overstuffed for a single domain. It mixes PDBe-specific tools (3) with a large set of general-purpose data tools, prediction market tools, subscriptions, and memory tools. This bloat suggests the server should be split into focused services.
For the stated PDBe domain, only three tools exist (get_molecules, get_summary, uniprot_mappings), missing essential operations like search, download, or advanced queries. The server's overall purpose is unclear, and it feels like a random collection of tools rather than a coherent API.