Pulse MCP Server
Bring Pulse traffic intelligence directly into your AI workflows.
We're introducing the Pulse MCP server, a Model Context Protocol interface for querying observed network traffic, requests, issues, PII signals, and aggregate metrics from Pulse-backed data.
Released: Feb 20, 2025
Available Now: Pulse MCP server support is available for AI-assisted troubleshooting and analysis workflows.
What's New
MCP Access to Core Pulse Resources
AI assistants can query structured data across:
Connections
Requests
Traffic (aggregates, availability, bandwidth, performance)
Issues (policy and API errors)
PII detections
Rich Tooling for Fast Investigation
The server exposes count/list/get/histogram/frequency patterns plus specialized tools for:
Request duration and tag analytics
Traffic summaries, time-series, location and geo breakdowns
Issue/error exploration
PII summaries and distributions
Filter-Driven Analysis
Use field-based and fuzzy filters (endpointId, vendorId, path, status, direction, etc.) to narrow investigations quickly.
Time-Aware Querying
Built-in support for RFC3339 timestamps and configurable granularity (minute to year) makes trend analysis straightforward.
Why It Matters
Pulse MCP turns raw traffic intelligence into conversational, automatable workflows for engineering, security, and operations teams:
Ask natural-language questions about live or recent traffic
Investigate incidents with reproducible query patterns
Build AI assistants that reason over real production telemetry
Reduce manual dashboard hopping during outages
Example Outcomes
"Which endpoints had the highest p99 latency in the last hour?"
"Show issue frequency by error for this vendor in prod"
"Count requests with auth failures and list affected paths"
"Summarize detected PII types by endpoint"
Feedback
Have ideas for new MCP tools or filters?
GitHub Issues: qpoint-io/qtap
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