27 tools. 8 can modify or destroy data without limits.
8 write tools that can modify data. Rate limits recommended.
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Write operations (add-to-knowledge-base, convert-to-pdf, generate-agent-completion) modify state. Without rate limits, an agent can make hundreds of changes in seconds — faster than any human can review or revert.
Execute tools (run-js-code, run-python-code) trigger processes with side effects. Builds, notifications, workflows — all fired without throttling.
Intercept sits between your agent and Dumpling AI MCP Server. 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 @Dumpling-AI/mcp-server-dumplingai add-to-knowledge-base:
rules:
- rate_limit: 30/hour Prevents bulk unintended modifications from agents caught in loops.
crawl:
rules:
- rate_limit: 60/minute Controls API costs and prevents retry loops from exhausting upstream rate limits.
The Dumpling AI MCP Server server has 6 write tools including add-to-knowledge-base, convert-to-pdf, generate-agent-completion. 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.
27 tools across 3 categories: Execute, Read, Write. 19 are read-only. 8 can modify, create, or delete data.
One line change. Instead of running the Dumpling AI MCP Server server directly, prefix it with Intercept: intercept -c dumpling-ai-mcp-server-dumplingai.yaml -- npx -y @Dumpling-AI/mcp-server-dumplingai. Download a pre-built policy from policylayer.com/policies/dumpling-ai-mcp-server-dumplingai and adjust the limits to match your use case.
Starter policies available for each. Same risk classification, same one-command setup.
Set budgets, approvals, and hard limits across MCP servers.
npx -y @policylayer/intercept init