Compute a Taylor/Laurent series expansion
AI agents invoke series_expansion to trigger actions in SageMath MCP Server. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call — builds kicked off, notifications sent, workflows started.
The tool triggers execution of SageMath code in a persistent computational session to compute a series expansion. While the operation appears mathematically benign (read-like in intent), it executes arbitrary symbolic computation in a stateful runtime environment. The persistent state and code-execution nature of the SageMath backend elevate this beyond a simple Read operation.
From the tool's definition 'Compute a Taylor/Laurent series expansion' — this runs a mathematical computation inside SageMath, which executes code in a persistent session
Documented attack patterns abuse exactly the kind of access series_expansion gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and SageMath MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for series_expansion:
{
"version": "1",
"default": "deny",
"tools": {
"series_expansion": {
"limits": [
{
"counter": "series_expansion_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
} series_expansion stays usable, but rate-capped — a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.
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Compute a Taylor/Laurent series expansion. It is categorised as a Execute tool in the SageMath MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the SageMath MCP Server MCP server in PolicyLayer and add a rule for series_expansion: 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 SageMath MCP Server. Nothing to install.
series_expansion is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the series_expansion 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 series_expansion. 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.
series_expansion is provided by the SageMath MCP Server MCP server (xbp-europe/sagemath-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from SageMath MCP Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
Free to start. No card required.
32 SageMath MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.