按机构ID分页查询机构投资案例，可按被投公司标签、行业和轮次筛选，适合回答某机构投过哪些具身智能、机器人、AI等标签公司；高权限套餐可查看未披露水下事件标识。
| Name | Required | Description | Default |
|---|---|---|---|
| cursor | No | ||
| fields | No | ||
| page_size | No | ||
| round_ids | No | ||
| scope_ids | No | ||
| investor_id | Yes | ||
| is_underwater | No | ||
| sub_scope_ids | No | ||
| company_tag_ids | No | ||
| company_tag_match_mode | No | union |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / properties / company_tag_idsAdded value: +{
+ "anyOf": [
+ {
+ "items": {
+ "type": "integer"
+ },
+ "type": "array"
+ },
+ {
+ "type": "null"
+ }
+ ],
+ "default": null,
+ "title": "Company Tag Ids"
+}Input schema / properties / company_tag_match_modeAdded value: +{
+ "default": "union",
+ "title": "Company Tag Match Mode",
+ "type": "string"
+}Input schema / properties / is_underwaterAdded value: +{
+ "anyOf": [
+ {
+ "type": "boolean"
+ },
+ {
+ "type": "null"
+ }
+ ],
+ "default": null,
+ "title": "Is Underwater"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It discloses pagination, filtering behaviors, and a permission-based behavior (undisclosed events). It does not mention idempotency, rate limits, or side effects, but adequately conveys it is a read operation.
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?
Description is concise, two sentences front-loading the main purpose and filters. Every word adds value, with no unnecessary repetition.
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 tool has 10 parameters and no annotations, the description covers the core functionality well and mentions the output schema existence (implied by context). However, it could elaborate on parameters like cursor and fields to be fully complete.
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%, so description must compensate. It explains filters for tags, industry, and round, which map to several parameters (company_tag_ids, scope_ids, round_ids, is_underwater). However, it does not explain parameters like cursor, fields, or company_tag_match_mode, leaving gaps.
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 verb (paginated query), resource (investment cases by institution ID), and available filters (tags, industry, round). It distinguishes from sibling tools like search_company_investment_cases by focusing on investor-specific cases.
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?
Description provides clear context on when to use (answering which companies an institution invested in) and mentions a permission-based limitation (high-permission packages can view undisclosed underwater events). However, it does not explicitly state when not to use or list 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 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.