List all projects with indexing summaries. Find a project by name or check which exist.
| Name | Required | Description | Default |
|---|---|---|---|
| feedback | No | Optional: report how a previous answer worked out; piggybacks on any call. |
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 useful behavioral context by stating the tool returns all projects and includes indexing summaries, which goes beyond 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?
Two short sentences deliver the core function and use cases with no filler. The main action is front-loaded, and every word adds value.
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 list-all operation with safety annotations already provided, the description is mostly complete. It could clarify how 'find by name' works given there is no name parameter, but the core behavior is adequately specified.
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 the optional feedback parameter is already documented. The description does not add parameter-level meaning, and the phrase 'find a project by name' could misleadingly imply a name parameter exists when the schema contains none. Baseline 3 is appropriate given high schema coverage.
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 and resource: 'List all projects with indexing summaries.' It clearly states the tool's core function and gives two concrete use cases, though it does not explicitly distinguish itself from sibling tool list_repositories.
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 implies when to use the tool ('find a project by name or check which exist'), but it does not explain when to prefer an alternative like list_repositories or how the two tools differ. Usage guidance is present but implicit rather than explicit.
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.
Tools generally target distinct operations—repository attachment, symbol resolution, graph traversal, source access, indexing health—and the detailed routing notes reduce ambiguity. A few pairs still overlap in intent (quick_lookup vs locate symbol, context vs ask_codebase), so it is not perfectly unambiguous.
All names are lowercase snake_case and readable, but the set mixes verb_noun patterns like add_repository and list_projects with single-word nouns/verbs like context, history, map, relate, and source, plus one acronym (adr). There is no predictable convention across the full surface, though individual names are clear.
25 tools is at the high end for a single MCP server and falls in the 'feels heavy' range. The breadth is justified by the code-intelligence/query domain, but the selection surface is large for an agent to navigate efficiently.
The code indexing, search, graph query, source access, history, ADR, test lookup, and scope estimation needs are well covered. Minor gaps remain—no detach/remove repository, no ADR content editing, and source access is gated by an add-on—but these are workable.