Mcp Numpy

29 tools. 29 can modify or destroy data without limits.

1 destructive tool with no built-in limits. Policy required.

Last updated:

29 can modify or destroy data
0 read-only
29 tools total
Read (0) Write / Execute (28) Destructive / Financial (1)

Destructive tools (np_squeeze) permanently delete resources. There is no undo. An agent calling these in a retry loop causes irreversible damage.

Write operations (np_arange, np_array, np_concatenate) modify state. Without rate limits, an agent can make hundreds of changes in seconds — faster than any human can review or revert.

One command. Full control.

Intercept sits between your agent and Mcp Numpy. Every tool call checked against your policy before it executes — so your agent can do its job without breaking things.

npx -y @policylayer/intercept scan -- npx -y @mcp-numpy
Scans every tool. Generates a policy. Starts enforcing.
Works with Claude Code · Cursor · Claude Desktop · Windsurf · any MCP client
Deny destructive operations
np_squeeze:
  rules:
    - action: deny

Destructive tools should never be available to autonomous agents without human approval.

Rate limit write operations
np_arange:
  rules:
    - rate_limit: 30/hour

Prevents bulk unintended modifications from agents caught in loops.

Can an AI agent delete data through the Mcp Numpy MCP server? +

Yes. The Mcp Numpy server exposes 1 destructive tools including np_squeeze. These permanently remove resources with no undo. Intercept blocks destructive tools by default so they never reach the upstream server.

How do I prevent bulk modifications through Mcp Numpy? +

The Mcp Numpy server has 28 write tools including np_arange, np_array, np_concatenate. Set rate limits in your policy file -- for example, rate_limit: 10/hour prevents an agent from making more than 10 modifications per hour. Intercept enforces this at the transport layer.

How many tools does the Mcp Numpy MCP server expose? +

29 tools across 2 categories: Destructive, Write. 0 are read-only. 29 can modify, create, or delete data.

How do I add Intercept to my Mcp Numpy setup? +

One line change. Instead of running the Mcp Numpy server directly, prefix it with Intercept: intercept -c io-github-daedalus-mcp-numpy.yaml -- npx -y @mcp-numpy. Download a pre-built policy from policylayer.com/policies/io-github-daedalus-mcp-numpy and adjust the limits to match your use case.

Other MCP servers with similar tools.

Starter policies available for each. Same risk classification, same one-command setup.

policylayer/intercept

Control every MCP tool call
your agent makes.

Set budgets, approvals, and hard limits across MCP servers.

npx -y @policylayer/intercept init
Protect your agent in 30 seconds. Scans your MCP config and generates enforcement policies for every server.
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