Low Risk

discovery_analyze

Run Disco on tabular data to find novel, statistically validated patterns. This is NOT another data analyst — it's a discovery pipeline that systematically searches for feature interactions, subgroup effects, and conditional relationships nobody thought to look for, then validates ea...

Handles credentials or secrets (api_key); High parameter count (11 properties)

Part of the Discovery Engine MCP server. Enforce policies on this tool with Intercept, the open-source MCP proxy.

AI agents call discovery_analyze to retrieve information from Discovery Engine without modifying any data. This is common in research, monitoring, and reporting workflows where the agent needs context before taking action. Because read operations don't change state, they are generally safe to allow without restrictions -- but you may still want rate limits to control API costs.

Even though discovery_analyze only reads data, uncontrolled read access can leak sensitive information or rack up API costs. An agent caught in a retry loop could make thousands of calls per minute. A rate limit gives you a safety net without blocking legitimate use.

Read-only tools are safe to allow by default. No rate limit needed unless you want to control costs.

leap-laboratories-discovery-engine.yaml
tools:
  discovery_analyze:
    rules:
      - action: allow

See the full Discovery Engine policy for all 12 tools.

Tool Name discovery_analyze
Category Read
Risk Level Low

View all 12 tools →

Agents calling read-class tools like discovery_analyze have been implicated in these attack patterns. Read the full case and prevention policy for each:

Browse the full MCP Attack Database →

Other tools in the Read risk category across the catalogue. The same policy patterns (rate-limit, allow) apply to each.

What does the discovery_analyze tool do? +

Run Disco on tabular data to find novel, statistically validated patterns. This is NOT another data analyst — it's a discovery pipeline that systematically searches for feature interactions, subgroup effects, and conditional relationships nobody thought to look for, then validates each on hold-out data with FDR-corrected p-values and checks novelty against academic literature. This is a long-running operation (3-15 minutes). Returns a run_id immediately. Use discovery_status to poll and discovery_get_results to fetch completed results. Use this when you need to go beyond answering questions about data and start finding things nobody thought to ask. Do NOT use this for summary statistics, visualization, or SQL queries. Public runs are free but results are published. Private runs cost credits. Call discovery_estimate first to check cost. Call discovery_upload first to upload your file, then pass the returned file_ref here. Args: target_column: The column to analyze — what drives it, beyond what's obvious. file_ref: The file reference returned by discovery_upload. analysis_depth: Search depth (1=fast, higher=deeper). Default 1. visibility: "public" (free) or "private" (costs credits). Default "public". title: Optional title for the analysis. description: Optional description of the dataset. excluded_columns: Optional JSON array of column names to exclude from analysis. column_descriptions: Optional JSON object mapping column names to descriptions. Significantly improves pattern explanations — always provide if column names are non-obvious (e.g. {"col_7": "patient age", "feat_a": "blood pressure"}). author: Optional author name for the report. source_url: Optional source URL for the dataset. api_key: Disco API key (disco_...). Optional if DISCOVERY_API_KEY env var is set. . It is categorised as a Read tool in the Discovery Engine MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on discovery_analyze? +

Add a rule in your Intercept YAML policy under the tools section for discovery_analyze. You can allow, deny, rate-limit, or validate arguments. Then run Intercept as a proxy in front of the Discovery Engine MCP server.

What risk level is discovery_analyze? +

discovery_analyze is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit discovery_analyze? +

Yes. Add a rate_limit block to the discovery_analyze rule in your Intercept 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.

How do I block discovery_analyze completely? +

Set action: deny in the Intercept policy for discovery_analyze. 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.

What MCP server provides discovery_analyze? +

discovery_analyze is provided by the Discovery Engine MCP server (leap-laboratories/discovery-engine). Intercept sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policies on Discovery Engine

Open source. One binary. Zero dependencies.

npx -y @policylayer/intercept
github.com/policylayer/intercept →
// GET IN TOUCH

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