search_crmSearch the authenticated business's CRM. The server chooses safe tenant-scoped queries; raw SQL and tenant identifiers are not accepted.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| query | Yes | ||
| entityTypes | No |
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 signal read-only safety; the description adds concrete behavioral detail: queries are tenant-scoped, chosen by the server, and raw SQL/tenant identifiers are rejected. This goes beyond the annotations and helps the agent understand what input will be accepted.
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 tight sentences: the first establishes purpose, the second adds an essential safety/input constraint. No filler or redundant restatement of annotations.
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?
Adequate for a simple search tool, but incomplete for a 3-parameter schema with no output schema: it doesn't describe how `entityTypes` narrows the search or what the result set looks like. The safety constraint is useful, yet parameter semantics and return behavior remain under-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 property descriptions are absent (0% coverage), and the description only broadly constrains the query (no raw SQL, no tenant IDs). It says nothing about `limit` or `entityTypes`, relying on the agent to infer their meaning from names and enum values.
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?
States a specific verb ('Search'), resource ('authenticated business's CRM'), and scopes it to tenant-safe behavior. This clearly distinguishes it from create/write or workspace tools. No ambiguity about what action it performs.
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?
Clear that this is the tool for searching the authenticated business's CRM. It doesn't name sibling tools or formal exclusions, but the CRM resource and safe-query constraint give adequate context for selection.
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.
Several tools overlap in purpose: get_workspace_overview and search_localtry_features both return feature/capability catalogs, and get_workspace_customization_status/list_workspace_versions overlap with customization history. run_localtry_command also acts as a generic catch-all that could subsume most of the specific action tools, making selection ambiguous.
Most tools follow a clear verb_noun pattern (get_*, search_*, create_*, run_*, list_*, restore_*, request_*). Minor deviations like create_or_update_crm_record and run_localtry_command introduce slight inconsistency, but the overall convention is predictable.
With 12 tools, the server is well-scoped for a platform that covers CRM, workflow agents, workspace customization, and feature discovery. Each tool addresses a distinct functional area without excessive fragmentation.
The surface covers the main workflows: CRM upsert/search, workflow agent creation and execution, customization request/status/version restore, and feature discovery. Some lifecycle gaps exist (no delete CRM record, no update/delete agent or workflow), but the generic run_localtry_command can partially compensate.