searchInfluencers
Search influencers by platform and follower count.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| platform | No | ||
| minFollowers | No |
Search influencers by platform and follower count.
| Name | Required | Description | Default |
|---|---|---|---|
| platform | No | ||
| minFollowers | 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?
No annotations are provided, so the description must disclose behavioral traits itself. It only states the basic search function without mentioning what is returned, whether results are filtered or listed, authentication requirements, or any side effects. For a read-only search tool, this lacks important transparency.
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, concise sentence that front-loads the action and resource. No filler or redundant information is present.
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 tool has no output schema and no annotations, so the description should provide sufficient context for invocation and expected results. It only states the search criteria, omitting the return format, pagination, or whether it returns a list or single result. The description is too sparse for a tool with no other contextual structure.
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 schema has 0% description coverage, so the description must compensate. It names the two parameters ('platform' and 'follower count') and explains they are search criteria, which adds meaning beyond the bare schema. However, it does not elaborate on expected values, constraints, or inclusivity of 'minFollowers'.
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 ('Search'), names the resource ('influencers'), and specifies the filtering criteria ('by platform and follower count'). This clearly distinguishes it from sibling tools focused on campaigns and submissions.
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 the tool is used for finding influencers based on platform and follower count, but it does not provide explicit when-to-use guidance or mention alternatives among sibling tools. It gives context but no exclusions.
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 targets a distinct resource and action: campaigns, submissions, benchmarks, pricing, actions, influencers. No two tools have overlapping purposes; even getBenchmarks vs getPricing are clearly separated by context.
All tool names follow a consistent verb_noun pattern in camelCase (e.g., createCampaign, listActions, reviewSubmission). The verbs are varied but the structure is uniform, making the set predictable.
10 tools is well within the ideal 3-15 range and matches the server's scope: campaign creation, stats, submissions, and reference lookups. Each tool earns its place without bloat.
Core lifecycle coverage is solid: create/list/get stats for campaigns, submit/review submissions. Minor gaps exist (no update/delete campaign, no single-submission detail view), but agents can work around them using existing tools.