OpenTelemetry Trace Latency Analyzer MCP, Ready to Go
Use Claude or Cursor with the OpenTelemetry Trace Latency Analyzer MCP to find and fix microservice bottlenecks instantly.
No credit card required. Experience the power of this integration risk-free.
Find and fix performance bottlenecks in your distributed microservices.
Works with every AI agent you already use
…and any MCP-compatible client
How fast is the OpenTelemetry Trace Latency Analyzer MCP Server?
Average time for the server to become ready for requests over the last 10 days, measured until the initialize / tools/list handshake completes. Metrics are updated daily between 00:00 and 04:00 UTC. Create a free account, use this MCP on Vinkius Cloud, and connect it to your AI agent in seconds.
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What AI agents can do with OpenTelemetry Trace Latency Analyzer (3 Tools) for Latency Analysis
Use these tools to identify bottlenecks, calculate self-time, and map out service latency distributions.
Get service distribution
Calculates the average latency for every service or span name in your trace. It helps you see which part of your stack is the heaviest.
Analyze trace latency
Breaks down the trace to show high-level metrics like total duration and span counts. It gives you a bird's-eye view of the request flow.
Identify bottlenecks
Flags specific spans that exceed a time threshold you set. This points you directly at the noisy neighbors or slow queries.
One MCP enables access. Vinkius turns MCPs into production-ready infrastructure.
You're looking at one of 5,800+ managed MCPs. The real value isn't the catalog. It's the control plane that secures, governs, audits, and manages every interaction between your agents and the tools they use.
No Shadow AI
Every agent action is visible, approved, and auditable. Nothing runs outside your governance.
Absolute agent control
Fine-grained permissions for every agent, MCP, and tool. Instantly revoke access and audit every execution.
Cost control per token
Spend broken down to the token, tool, and agent. Budgets and hard limits. No surprise invoices.
Managed & monitored infra
We operate the runtime, authentication, scaling, retries, and monitoring. Your team manages AI, not infrastructure.
Data protection, DLP by design
Sensitive data is filtered before reaching the model. Access is governed so agents receive only the information they're allowed to use.
Token optimization, real savings
Lower AI costs by delivering the right context instead of unnecessary tools. Better accuracy, faster responses, and fewer wasted tokens.
OpenTelemetry Trace Latency Analyzer for Bottleneck Detection
This is for the engineers who live in the weeds of distributed systems. It's for the people who need to prove exactly where a bottleneck is located without spending hours manually calculating spans.
SRE
The person getting paged at 3 AM because a core API is lagging and needs to find the culprit fast.
Backend Developer
The engineer trying to optimize a complex microservice chain and needing to see where the time is actually spent.
Performance Engineer
The specialist tasked with shaving milliseconds off a global request by identifying the heaviest spans.
DevOps Engineer
The person managing high-traffic infrastructure who needs to justify scaling needs with hard latency data.
Frequently Asked Questions
Can the OpenTelemetry Trace Latency Analyzer help with microservices? +
Yes, it is specifically designed for distributed traces. It helps you see how requests move between different services and where the time is being lost.
How do I find the slowest part of a trace using this MCP? +
The MCP automatically identifies bottlenecks by looking for spans that exceed your time limits and highlighting the longest chains of dependencies.
Does it show how much time a service spends on its own work? +
Yes, it calculates per-span self-time. This allows you to see if a service is actually slow or just waiting for a downstream response.
Can it help me find out why my API is slow? +
Absolutely. By analyzing the trace spans, it identifies the critical path and provides a distribution of latency across your entire architecture.
What kind of data does the OpenTelemetry Trace Latency Analyzer need? +
It requires OpenTelemetry-style trace data, specifically spans that include start and end timestamps along with parent-child IDs.
Does it work with multiple services at once? +
Yes, it can analyze traces involving dozens of different services and give you a percentage-based breakdown of where the time is going.
What kind of trace data does this tool support? +
It supports OpenTelemetry-style traces where each span includes a unique identifier, parent ID, service name, span name, and start/end timestamps.
How can I identify the slowest parts of my request? +
By using identify_bottlenecks, you can find spans that exceed a specific latency threshold within your trace data.
Can I see how much time each service contributes to the total trace? +
Yes, using get_service_distribution allows you to see an aggregation of average latency per service or span name.
Your AI, connected to everything.
No credit card required · Free tier available
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