Intra-function dataflow analysis: track how each parameter flows through the function body — into which calls, where it gets mutated, and what is returned. Phase 1: single function scope. Use to understand data transformations within a function. For security-focused data flow use taint_analysis i...
AI agents call get_dataflow to retrieve information from Trace without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool performs static analysis of source code to trace parameter flow within function bodies. It retrieves and queries information about data dependencies and transformations without side effects. The explicit 'Read-only' designation confirms it performs queries and analysis only, returning JSON representation of dataflow patterns. No code execution, modification, deletion, or financial impact possible.
From the tool's definition Description explicitly states 'Read-only' and 'track how each parameter flows through the function body'. Returns JSON data about dataflow without modifying any source code or state.
Documented attack patterns abuse exactly the kind of access get_dataflow gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Trace, and nothing reaches the server without passing your rules. This is the rule we recommend for get_dataflow:
{
"version": "1",
"default": "deny",
"tools": {
"get_dataflow": {}
}
}get_dataflow is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
Free to start. No card required.
Intra-function dataflow analysis: track how each parameter flows through the function body — into which calls, where it gets mutated, and what is returned. Phase 1: single function scope. Use to understand data transformations within a function. For security-focused data flow use taint_analysis instead. Read-only. Returns JSON: { symbol_id, params: [{ name, flows: [{ target, mutated }] }], returnPaths }. It is categorised as a Read tool in the Trace MCP Server, which means it retrieves data without modifying state.
Register the Trace MCP server in PolicyLayer and add a rule for get_dataflow: 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 Trace. Nothing to install.
get_dataflow 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 get_dataflow 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 get_dataflow. 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.
get_dataflow is provided by the Trace MCP server (nikolai-vysotskyi/trace-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 178 Trace tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
Free to start. No card required.
178 Trace tools catalogued and risk-classified — across an index of 42,500+ MCP servers.