Today's summary of the official Model Context Protocol server registry. Returns total servers, by-status breakdown, top namespaces, and 1-day deltas (newly added, reactivated, deprecated). Captured daily at 9:30 AM UTC from registry.modelcontextprotocol.io. Useful when an agent wants to see how t...
Part of the TensorFeed MCP server. Enforce policies on this tool with Intercept, the open-source MCP proxy.
AI agents call mcp_registry_snapshot to retrieve information from TensorFeed without modifying any data. This is common in research, monitoring, and reporting workflows where the agent needs context before taking action. Because read operations don't change state, they are generally safe to allow without restrictions -- but you may still want rate limits to control API costs.
Even though mcp_registry_snapshot only reads data, uncontrolled read access can leak sensitive information or rack up API costs. An agent caught in a retry loop could make thousands of calls per minute. A rate limit gives you a safety net without blocking legitimate use.
Read-only tools are safe to allow by default. No rate limit needed unless you want to control costs.
tools:
mcp_registry_snapshot:
rules:
- action: allowSee the full TensorFeed policy for all 42 tools.
Agents calling read-class tools like mcp_registry_snapshot have been implicated in these attack patterns. Read the full case and prevention policy for each:
Other tools in the Read risk category across the catalogue. The same policy patterns (rate-limit, allow) apply to each.
Today's summary of the official Model Context Protocol server registry. Returns total servers, by-status breakdown, top namespaces, and 1-day deltas (newly added, reactivated, deprecated). Captured daily at 9:30 AM UTC from registry.modelcontextprotocol.io. Useful when an agent wants to see how the MCP ecosystem is growing or detect freshly-deprecated servers it may be using. Free, no auth.. It is categorised as a Read tool in the TensorFeed MCP Server, which means it retrieves data without modifying state.
Add a rule in your Intercept YAML policy under the tools section for mcp_registry_snapshot. You can allow, deny, rate-limit, or validate arguments. Then run Intercept as a proxy in front of the TensorFeed MCP server.
mcp_registry_snapshot 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 mcp_registry_snapshot rule in your Intercept 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 Intercept policy for mcp_registry_snapshot. 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.
mcp_registry_snapshot is provided by the TensorFeed MCP server (@tensorfeed/mcp-server). Intercept sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic policy on every MCP tool call. Per-identity grants. Full audit log.