AgentBio
Server Details
Biomedical compound and drug intelligence — PubChem compound data (formula, SMILES, structure), OpenFDA drug labels & adverse events, and ChEMBL bioactivity & target data. Built for pharma research and biotech agents.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
Glama MCP Gateway
Connect through Glama MCP Gateway for full control over tool access and complete visibility into every call.
Full call logging
Every tool call is logged with complete inputs and outputs, so you can debug issues and audit what your agents are doing.
Tool access control
Enable or disable individual tools per connector, so you decide what your agents can and cannot do.
Managed credentials
Glama handles OAuth flows, token storage, and automatic rotation, so credentials never expire on your clients.
Usage analytics
See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.
Tool Definition Quality
Average 3.2/5 across 3 of 3 tools scored.
Each tool queries a distinct database (PubChem, OpenFDA, ChEMBL) for different types of information: compound properties, drug labeling/safety, and drug targets respectively. There is no overlap in purpose.
All three tools follow the consistent pattern 'get_<specific_noun>', using snake_case and a clear verb-noun structure that is uniform across the set.
Three tools are perfectly scoped for a specialized drug information server, providing essential data from three key public databases without redundancy.
The set covers core drug information (compound, regulatory, target). Minor gaps exist, such as lack of clinical trial data or drug-to-drug interaction queries, but the major knowledge areas are addressed.
Available Tools
3 toolsget_compound_dataBInspect
Get drug/compound data from PubChem (NIH). Returns CID, IUPAC name, molecular formula, molecular weight, canonical SMILES, InChI, description, and synonyms.
| Name | Required | Description | Default |
|---|---|---|---|
| cid | No | PubChem CID number (alternative to name) | |
| name | No | Drug or compound name (e.g. aspirin, caffeine, ibuprofen) | aspirin |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden for behavioral traits. It only mentions the source (PubChem/NIH) and return fields, but omits important details like whether an API key is needed, rate limits, or that the operation is read-only.
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 a single, clear sentence that front-loads the core purpose and immediately lists returned data. Every word serves a purpose; no redundancy.
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?
The description covers the main purpose and return fields, but lacks key operational details: parameter dependencies (at least one of cid/name needed?), default behavior (aspirin), error handling, and output structure. Given low complexity, it is adequate but not thorough.
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 description coverage is 100%, so baseline is 3. The description adds minimal value beyond the schema, only providing examples (aspirin) and listing return fields, which do not directly enhance parameter understanding.
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 drug/compound data from PubChem and lists specific return fields. It distinguishes itself from sibling tools by focusing on chemical compound properties, though the verb 'Get' is generic.
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 siblings like get_drug_info or get_drug_targets. The description only states what it does, not when it's appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_drug_infoBInspect
Get drug label, safety info, adverse events, or recall data from OpenFDA. Returns brand names, generic name, indications, warnings, dosage, interactions.
| Name | Required | Description | Default |
|---|---|---|---|
| name | No | Drug name (e.g. metformin, aspirin, lisinopril) | metformin |
| type | No | label (default), adverse_events, or recalls | label |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must fully disclose behavior. It states what is returned (brand names, warnings, etc.) but fails to mention important traits such as whether the operation is read-only, any rate limits, authentication requirements, or side effects (e.g., data freshness, pagination). The description implies it is a safe query, but the lack of explicit behavioral context is a gap.
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 concise at two sentences, with the main purpose front-loaded. Every sentence adds value: first sentence states the action and data source, second lists returned information. No unnecessary words.
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 the tool's low complexity (2 parameters, no nested objects) and no output schema, the description covers the essential aspects: what the tool does, what it returns, and parameter details. It could mention return format or any limitations (e.g., number of results), but overall it is sufficiently complete for straightforward use.
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 input schema has 100% coverage, and the description adds meaningful context beyond the schema: it provides a concrete example for the 'name' parameter (metformin) and explains the options for 'type' (label, adverse_events, recalls). This helps the agent understand parameter usage beyond raw schema definitions.
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 identifies the tool's purpose: retrieving drug label, safety info, adverse events, or recall data. It specifies the data source (OpenFDA) and lists returned fields. However, it does not explicitly differentiate from sibling tools like get_compound_data or get_drug_targets, leaving some ambiguity about when to use this tool over them.
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 (e.g., get_compound_data, get_drug_targets). The description lacks any 'when to use' or 'when not to use' context, forcing the agent to guess based on names alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_drug_targetsBInspect
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) |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. The description discloses return data types but does not mention safety, permissions, rate limits, or that it is likely a read operation. Adequately transparent for a simple data retrieval 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?
Two sentences with no redundant words. Front-loads the core purpose. Could be slightly more concise but is efficient.
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?
Lists return fields adequately for a tool with no output schema, but omits that the 'type' parameter changes output format. Also does not address sibling tool differences.
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 parameter descriptions. The description adds no additional meaning beyond the schema, so baseline 3 is appropriate.
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 function (Get drug target and bioactivity data) and lists return fields, but does not differentiate from sibling tools get_compound_data and get_drug_info, which may have overlapping purposes.
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 on when to use this tool vs alternatives, no exclusions or prerequisites mentioned. The sibling tools are named but not explained.
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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