"What's the ticker for…" / "find the CIK for…" / "what's the RxCUI for…" / "look up the ID for…" / "what is X's official identifier" — resolve a user-spoken NAME to the canonical/official identifier other tools require as input. Use FIRST whenever you have a name but need an ID. SUPPORTED TYPES: ...
AI agents call resolve_entity to retrieve information from Mcp Semanticscholar without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
type | string | Yes | Entity type: "company" or "drug". |
value | string | Yes | For company: ticker (AAPL), CIK (0000320193), or name. For drug: brand or generic name (e.g., "ozempic", "metformin"). |
Parameters from the server's own tool schema.
This tool purely resolves names to canonical identifiers (tickers, CIKs, RxCUIs) by querying external registries. It is a read/lookup operation with no side effects, no data modification, and no destructive or financial actions. Misuse potential is minimal as it only returns identifier mappings.
From the tool's definition resolve a user-spoken NAME to the canonical/official identifier — look up the ID for… what is X's official identifier
Attacks that exploit this kind of access
"What's the ticker for…" / "find the CIK for…" / "what's the RxCUI for…" / "look up the ID for…" / "what is X's official identifier" — resolve a user-spoken NAME to the canonical/official identifier other tools require as input. Use FIRST whenever you have a name but need an ID. SUPPORTED TYPES: "company" (returns ticker + 10-digit CIK + company_name from SEC EDGAR + pipeworx://edgar/company/{cik} citation URI; accepts ticker, CIK, or company name as input — auto-disambiguated), "drug" (returns RxCUI + ingredient + brand from RxNorm + pipeworx://rxnorm/{rxcui} citation; accepts brand or generic name). Each call cascades through several lookup endpoints internally — using resolve_entity replaces 2-3 manual lookups. It is categorised as a Read tool in the Mcp Semanticscholar MCP Server, which means it retrieves data without modifying state.
resolve_entity accepts 2 parameters: type, value. Required: type, value. The full parameter table on this page comes from the server's own tool schema.
Register the Mcp Semanticscholar MCP server in PolicyLayer and add a rule for resolve_entity: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Mcp Semanticscholar. Nothing to install.
resolve_entity is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the resolve_entity rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for resolve_entity. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
resolve_entity is provided by the Mcp Semanticscholar MCP server (https://gateway.pipeworx.io/semanticscholar/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
Teams ship this data inside their own products. See what a licence covers →