math_eval
Evaluates arithmetic with correct operator precedence, parentheses, exponentiation, factorials, named variables and 30+ functions. Language models perform arithmetic by pattern-matching and quietly get long multiplications and compounding wrong; this computes the number instead of predicting it.
This record as markdown: /tools/com-fluentedi-tools/math-eval.md
What math_eval does on Tools
AI agents call math_eval to retrieve information from Tools 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 |
|---|---|---|---|
precision | integer | — | Decimal places to round the formatted result to. |
variables | object | — | Named values usable in the expression, e.g. {"rate": 0.07}. |
expression | string | Yes | Expression to evaluate, e.g. "(1+0.07)^30 * 1000". |
Parameters from the server's own tool schema.
Why math_eval is rated Low
Even though math_eval only reads data, uncontrolled read access leaks sensitive information and racks up API costs: an agent caught in a retry loop can make thousands of calls a minute without anyone noticing.
Risk signalsAccepts freeform code/query input (expression)
Attacks that exploit this kind of access
The rule that runs math_eval safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Tools, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For math_eval, this is the rule to start with:
math_eval 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 Tools, apply this rule, and every math_eval call is checked against it from then on.
Questions about math_eval
Evaluates arithmetic with correct operator precedence, parentheses, exponentiation, factorials, named variables and 30+ functions. Language models perform arithmetic by pattern-matching and quietly get long multiplications and compounding wrong; this computes the number instead of predicting it. It is categorised as a Read tool in the Tools MCP Server, which means it retrieves data without modifying state.
math_eval accepts 3 parameters: precision, variables, expression. Required: expression. The full parameter table on this page comes from the server's own tool schema.
Register the Tools MCP server in PolicyLayer and add a rule for math_eval: 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 Tools. Nothing to install.
math_eval 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 math_eval 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 math_eval. 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.
math_eval is provided by the Tools MCP server (https://fluentedi.com/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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