splitifi_predict_litigation
Predict Litigation Analytics case outcome using ML models trained on 3.52B+ court records. Provide jurisdiction and case_facts (case_type, court_level, amount_in_controversy, discovery_complexity).
This record as markdown: /tools/io-github-mysplitifi-splitifi-mcp/splitifi-predict-litigation.md
What splitifi_predict_litigation does on Splitifi Intelligence MCP
AI agents call splitifi_predict_litigation to retrieve information from Splitifi Intelligence MCP 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 |
|---|---|---|---|
judge_id | string | — | Optional — judge ID for judge-specific modifier |
case_facts | object | Yes | Case details for Litigation Analytics. Key fields: case_type, court_level, amount_in_controversy, discovery_complexity |
jurisdiction | string | Yes | State/province/country code, e.g. "TX", "CA", "ON" |
Parameters from the server's own tool schema.
Why splitifi_predict_litigation is rated Low
This tool reads/queries ML model predictions based on structured case inputs. While the underlying models are trained on sensitive legal data (court records) and predictions could influence high-stakes litigation decisions, the tool itself has no side effects—it does not execute code, make financial transactions, modify case records, or trigger external operations.
From the tool's definition The tool 'predict Litigation Analytics case outcome using ML models' retrieves and queries predictive data derived from court records.
Attacks that exploit this kind of access
The rule that runs splitifi_predict_litigation safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Splitifi Intelligence MCP, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For splitifi_predict_litigation, this is the rule to start with:
splitifi_predict_litigation 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 Splitifi Intelligence MCP, apply this rule, and every splitifi_predict_litigation call is checked against it from then on.
Questions about splitifi_predict_litigation
Predict Litigation Analytics case outcome using ML models trained on 3.52B+ court records. Provide jurisdiction and case_facts (case_type, court_level, amount_in_controversy, discovery_complexity). It is categorised as a Read tool in the Splitifi Intelligence MCP MCP Server, which means it retrieves data without modifying state.
splitifi_predict_litigation accepts 3 parameters: judge_id, case_facts, jurisdiction. Required: case_facts, jurisdiction. The full parameter table on this page comes from the server's own tool schema.
Register the Splitifi Intelligence MCP server in PolicyLayer and add a rule for splitifi_predict_litigation: 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 Splitifi Intelligence MCP. Nothing to install.
splitifi_predict_litigation 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 splitifi_predict_litigation 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 splitifi_predict_litigation. 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.
splitifi_predict_litigation is provided by the Splitifi Intelligence MCP server (splitifi-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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