competitive_deep_dive_async
Async variant of competitive_deep_dive. Returns immediately (<200ms) with a job_id. The research runs in the background (p50≈25s, p95≈30s for depth=medium). Poll the result with competitive_deep_dive_result(job_id) after the eta_seconds hint. Use this instead of competitive_deep_dive when the age...
This record as markdown: /tools/io-github-getgapup-mcp-knowledge/competitive-deep-dive-async.md
What competitive_deep_dive_async does on Mcp Knowledge
AI agents call competitive_deep_dive_async to retrieve information from Mcp Knowledge without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
depth | string | — | Research depth: 'easy'≈15s, 'medium'≈30s (default), 'hard'≈60s |
company | string | Yes | Name or domain of the target company (e.g. 'Salesforce', 'notion.so') |
competitors | array | — | Optional list of competitor names or domains to include in the comparison matrix (max 5) |
Parameters from the server's own tool schema.
Why competitive_deep_dive_async is rated Low
This is a querying/research tool that retrieves competitive intelligence metadata and analysis. It has no ability to modify, delete, or financially commit resources. The 'medium' severity accounts for potential misuse in competitive intelligence gathering (e.g., targeting or manipulation based on analysis), but the tool itself is fundamentally a read operation that collects and returns business data with no side…
From the tool's definition Returns analysis data asynchronously with job_id polling; described as 'research runs in the background' and 'poll the result' — no modifications to data or external systems mentioned.
Attacks that exploit this kind of access
The rule that runs competitive_deep_dive_async safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Mcp Knowledge, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For competitive_deep_dive_async, this is the rule to start with:
competitive_deep_dive_async is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Mcp Knowledge, apply this rule, and every competitive_deep_dive_async call is checked against it from then on.
Questions about competitive_deep_dive_async
Async variant of competitive_deep_dive. Returns immediately (<200ms) with a job_id. The research runs in the background (p50≈25s, p95≈30s for depth=medium). Poll the result with competitive_deep_dive_result(job_id) after the eta_seconds hint. Use this instead of competitive_deep_dive when the agent cannot wait >15s for a response. Inputs: same as competitive_deep_dive — company (required), competitors (optional list, max 5), depth (easy/medium/hard, default medium). Async tool — register a webhook via webhooks_manage(register, url, [job.completed]) to receive callbacks instead of polling. Faster + lighter. It is categorised as a Read tool in the Mcp Knowledge MCP Server, which means it retrieves data without modifying state.
competitive_deep_dive_async accepts 3 parameters: depth, company, competitors. Required: company. The full parameter table on this page comes from the server's own tool schema.
Register the Mcp Knowledge MCP server in PolicyLayer and add a rule for competitive_deep_dive_async: 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 Knowledge. Nothing to install.
competitive_deep_dive_async 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 competitive_deep_dive_async 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 competitive_deep_dive_async. 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.
competitive_deep_dive_async is provided by the Mcp Knowledge MCP server (https://mcp.gapup.io). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
More on Mcp Knowledge, and thousands of servers like it.
This server
Across the catalogue