openinference-instrumentation-mcp
OpenInference MCP Instrumentation
Decision gist · record as of 2026-08-14
Yes, if you are already using MCP with Python and need distributed tracing or observability. The low install friction, active maintenance, permissive license, and zero known vulnerabilities make it a safe addition. Install it only if you have an OpenTelemetry collector or observability platform in place to consume the context propagation it enables.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later (supports up to 3.14); OpenTelemetry API and instrumentation packages must be installed.
- Low friction installation with a pure-Python wheel.
- Actively maintained as of 2026-08-14 with recent release history; no known vulnerabilities.
License · maintenance · safety
Apache-2.0 (permissive) — Apache-2.0 permissive license allows use in commercial and proprietary projects with minimal restrictions.
last release 2026-08-01 (13 days) · last repo commit 2026-08-14 · 1,147 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 192,976 downloads/mo, #9,854 on PyPI
Alternatives
Verify before relying
pip install openinference-instrumentation-mcp
from openinference.instrumentation.mcp import MCP_INSTRUMENTATION
from opentelemetry import trace
# Instrumentation enables context propagation for MCP tool calls
MCP_INSTRUMENTATION.instrument()- Whether context propagation works with all MCP SDK versions or has version constraints beyond the package metadata.
- Performance overhead of instrumentation in high-throughput MCP tool call scenarios.
- Compatibility with non-OpenTelemetry tracing backends or observability platforms.
What it is and what it does
This package adds OpenTelemetry instrumentation to the MCP Python SDK, enabling distributed tracing by propagating trace context from the caller into MCP tool executions. It integrates with the OpenInference framework and observability platforms like Arize Phoenix and Arize AX. Currently, it focuses on context propagation rather than generating new telemetry data itself—the primary use case is connecting existing spans across MCP boundaries so that tool calls and their execution can be viewed as part of a single trace.
The package depends on openinference-instrumentation, opentelemetry-api, opentelemetry-instrumentation, and wrapt. It is marked as Production/Stable and actively maintained, with support for modern Python versions.
Use it for
- Connect traces from an LLM application into MCP tool executions for end-to-end observability.
- Debug MCP tool call latency and failures by viewing them in the context of the parent request trace.
- Correlate MCP tool behavior with upstream application logic in a distributed tracing platform.
- Monitor MCP tool call patterns and performance metrics through OpenTelemetry-compatible backends.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you are already using MCP with Python and need distributed tracing or observability.
The low install friction, active maintenance, permissive license, and zero known vulnerabilities make it a safe addition. Install it only if you have an OpenTelemetry collector or observability platform in place to consume the context propagation it enables.
Install
openinference-instrumentation-mcp on PyPI
Before you install
Low friction installation with a pure-Python wheel. Actively maintained as of 2026-08-14 with recent release history; no known vulnerabilities.
Requires Python 3.10 or later (supports up to 3.14); OpenTelemetry API and instrumentation packages must be installed.
License in practice
Apache-2.0 permissive license allows use in commercial and proprietary projects with minimal restrictions.
Quickstart
pip install openinference-instrumentation-mcp
from openinference.instrumentation.mcp import MCP_INSTRUMENTATION
from opentelemetry import trace
# Instrumentation enables context propagation for MCP tool calls
MCP_INSTRUMENTATION.instrument()Verify before relying
- Whether context propagation works with all MCP SDK versions or has version constraints beyond the package metadata.
- Performance overhead of instrumentation in high-throughput MCP tool call scenarios.
- Compatibility with non-OpenTelemetry tracing backends or observability platforms.
Package facts
| License | Apache-2.0 permissive |
| Python support | Supports the current Python release <3.15,>=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 4 packagesopeninference-instrumentationopentelemetry-apiopentelemetry-instrumentationwrapt |
| Maintenance | Actively maintained 13 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 192,976 / month, #9,854 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableIntended Audience :: DevelopersLicense :: OSI Approved :: Apache Software LicenseProgramming Language :: PythonProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14 |
Evidence: openinference_instrumentation_mcp-2.0.5-py3-none-any.whl
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See also openinference-instrumentation-openai · openinference-instrumentation-claude-agent-sdk · openinference-instrumentation · openinference-instrumentation-google-adk · openinference-instrumentation-dspy · openinference-instrumentation-openai-agents · openinference-instrumentation-agno · opentelemetry-instrumentation-mcp · openinference-instrumentation-bedrock · opentracing