按公司ID查询公司画像，包括公司简称、工商全称 registered_name、行业、标签、地区、简介、最新融资和历史投资方等字段；工商名称、工商注册名称均对应 registered_name。
| Name | Required | Description | Default |
|---|---|---|---|
| fields | No | ||
| company_id | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
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?
With no annotations, the description indicates the tool is a read-only query by listing returned fields, but does not explicitly state safety, side effects, or authentication needs.
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 sentences with clear purpose and field list, front-loaded with action and resource. No wasted words.
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?
Covers main fields and clarifies registered_name mapping. Output schema exists, so structure details are not needed. Lacks mention of pagination or limits, but acceptable for a simple query.
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 coverage is 0%, but description adds context for company_id and lists possible response fields; however, it does not explain the 'fields' parameter for selecting subsets.
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?
Description clearly states the tool queries company profile by company ID and lists key fields returned. It distinguishes itself from sibling tools like get_company_funding_events by focusing on the broader profile, but does not explicitly differentiate.
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 usage when a company profile is needed by ID, but provides no guidance on when to use alternatives or when not to use this tool.
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: counting vs searching vs retrieving profiles vs ranking vs resolving. There is no ambiguity as tools like count_companies and search_companies have clearly separated purposes (count vs list). Even similar tools like search_companies and search_closed_companies are distinguished by company status.
All tool names follow the verb_noun pattern (e.g., search_companies, get_company_profile, resolve_companies) using snake_case consistently. The naming is predictable and clear, with only minor variations like aggregate_funding_by_tags which still starts with a verb.
With 17 tools, the server covers a comprehensive set of operations for a company/funding database without being overwhelming. Each tool serves a specific need, and the count aligns well with the domain's complexity.
The tool set covers all major operations for querying companies, funding, investors, events, FA cases, tags, and lookups. It includes both aggregated counts and detailed listings, ranking, and name resolution. No obvious gaps for a read-only data retrieval server.
