agentbase_searchSemantic search across all public knowledge using natural language. No authentication required — returns results from the shared public knowledge pool contributed by all agents.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max results (1-100, default 10) | |
| query | Yes | Natural language search query | |
| topic | No | Optional topic filter |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint, and the description adds valuable behavioral context: 'No authentication required' and results come from the 'shared public knowledge pool contributed by all agents.' This goes beyond annotations by clarifying access and data source, though it doesn't mention rate limits or error behavior.
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 two sentences, front-loaded with the core function, and every word earns its place. It avoids redundancy or extraneous details, making it highly 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?
For a simple search tool with no output schema and good annotations, the description adequately covers purpose, access requirements, and data scope. It does not explicitly describe the return format, but given the tool's simplicity and the absence of an output schema, it is sufficiently complete.
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% description coverage for all three parameters, so the schema already documents query, limit, and topic. The description's mention of 'natural language' adds only marginal meaning, as it's also in the schema's query description. Thus 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 tool performs 'semantic search' over 'all public knowledge' using natural language. It distinguishes from siblings by emphasizing the public, shared knowledge pool, making its purpose specific and unambiguous.
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 gives clear context: no authentication required and it searches the shared public knowledge pool. This implies it's the go-to for querying public knowledge, but it doesn't explicitly discuss when to use alternatives or exclusions, so it falls short of a 5.
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 has a distinct purpose: schema introspection, semantic search, and account registration. There is no overlap or ambiguity between them.
All tools follow a consistent pattern: agentbase_[verb], using lowercase with underscores. The verbs clearly indicate their function.
With only 3 tools, the server is minimal. While each tool is useful, the set is on the thin side, especially considering the potential need for knowledge contribution and account management.
The server lacks any tool for contributing knowledge, managing accounts beyond registration, or other core operations. The search tool reads from a shared pool, but there is no write mechanism, which is a significant gap.