Find and verify open-source AI projects from explicit requirements.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | ||
| locale | No | en | |
| request_id | No | ||
| constraints | No |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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 declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds the 'verify' behavior, but does not explain what verification entails, whether it performs external lookups, or how failures are handled. This is acceptable but minimal given the annotations.
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?
One front-loaded sentence with no filler and no redundant restatement of the title. The brevity is an asset, though it contributes to the lack of usage and parameter guidance.
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 4-parameter schema, the existence of sibling tools, and the output schema, this description is too sparse. It omits guidance on when to prefer search_ai_projects over browse_radar_projects, how to structure requirements, and what 'verify' concretely means. The output schema covers return values, but the tool is not fully self-describing.
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 0%; query, locale, and request_id are not explained in the schema except enum values. The description's 'explicit requirements' aligns with the constraints parameter, but it does not say how to use query versus constraints, what locale changes, or what request_id is for. The description does not compensate for the schema gap.
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 uses a specific verb pair, 'Find and verify,' and names the resource, 'open-source AI projects,' along with the source of requirements. It is clearer than the bare title and hints at a validation role. However, it does not explicitly distinguish itself from browse_radar_projects, so an agent may still be unsure whether to search or browse.
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 phrase 'from explicit requirements' implies this tool is for targeted searches where the user has concrete criteria. No when-not guidance or alternative tool names are given, so the description does not help an agent decide between this and browse_radar_projects or find_alternatives.
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 generally distinct role: browsing radar views, searching projects, getting facts, comparing, composing stacks, and finding alternatives. A couple of tools—notably browse_radar_projects and search_ai_projects—could be confused, but their descriptions clarify exploratory browsing versus requirement-driven search.
All tool names follow a consistent snake_case verb_noun pattern: browse_*, get_*, search_ai_projects, compare_ai_projects, compose_ai_stack, find_alternatives. The naming makes the action and target object immediately clear across the entire set.
Nine tools is a well-scoped size for an open-source AI intelligence and decision-support server. Each tool covers a distinct part of the workflow without feeling bloated or redundant.
The set covers the main workflow well: overview, browsing, search, project facts, license evidence, comparison, stack composition, and alternatives. Minor gaps like project tracking/history or export utilities are non-essential for this kind of intelligence/decision-support surface.