Get drug target and bioactivity data from ChEMBL (EMBL-EBI). Returns ChEMBL ID, max clinical phase, molecule type, molecular properties, and indication class.
| Name | Required | Description | Default |
|---|---|---|---|
| name | No | Drug or compound name (e.g. ibuprofen, atorvastatin) | ibuprofen |
| type | No | molecule (default) or activity | molecule |
| chembl_id | No | ChEMBL ID for activity lookup (e.g. CHEMBL521) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses what data is returned (ChEMBL ID, clinical phase, etc.), which is useful. However, with no annotations, it does not disclose potential variations in behavior (e.g., how the 'type' parameter changes results), auth requirements, or whether results are singular or list-based. Moderate transparency for a read-only tool.
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 one concise sentence, front-loads the main action, and includes the most relevant return information. No redundant or filler content.
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?
Despite having no output schema and no annotations, the description does not explain how the optional parameters affect the request or what to expect when using 'type=activity'. It lists return fields but leaves important behavioral context (e.g., required vs optional inputs, mode differences) unaddressed. The tool is simple, but the description is incomplete for an agent to use it effectively in all valid configurations.
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?
The schema already provides 100% description coverage for all three parameters, so the description adds little beyond the schema. It does not clarify parameter dependencies or how 'type' interacts with 'name'/'chembl_id', but the schema descriptions are adequate, warranting the baseline 3.
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 it gets drug target and bioactivity data from ChEMBL, using a specific verb and resource. It lists return fields, but it does not explicitly distinguish itself from sibling tools like get_compound_data or get_drug_info, so it falls short of a 5.
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?
No guidance is provided on when to use this tool versus alternatives. It does not mention scenarios, exclusions, or sibling tool differentiators. The description is purely declarative with no usage context.
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.
Each tool targets a distinct data source and aspect: PubChem for chemical compound data, OpenFDA for regulatory and safety info, and ChEMBL for target and bioactivity data. There is no overlap in their purposes, making selection unambiguous.
All tools follow a consistent get_<object>_<data_type> pattern: get_compound_data, get_drug_info, get_drug_targets. The verb is always 'get' and the uses snake_case throughout, creating a predictable and uniform naming scheme.
With only 3 tools, the server is compact but covers three major drug-related databases. While a few more tools might round out the domain, the current count is reasonable and each tool earns its place.
The server covers chemical data, regulatory/safety information, and target/bioactivity data, providing a solid core for drug information retrieval. It lacks some common operations like search or batch retrieval, but for the stated purpose of getting specific data, the coverage is strong.