MCPInstall

sentry-python-sdk

Full Sentry SDK setup for Python. Use when asked to "add Sentry to Python", "install sentry-sdk", "setup Sentry in Python", or configure error monitoring, tracing, profiling, logging, metrics, crons, or AI monitoring for Python applications. Supports Django, Flask, FastAPI, Celery, Starlette, AIOHTTP, Tornado, and more.

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Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/getsentry/sentry-agent-skills --skill sentry-python-sdk
  1. 01

    Install

    Run the command in your project. The CLI asks which agents to install for.

  2. 02

    Describe the task

    Ask your agent for something this skill covers. It loads sentry-python-sdk automatically when relevant.

  3. 03

    Review the result

    The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

Sentry Python SDK

Opinionated wizard that scans your Python project and guides you through complete Sentry setup.

Invoke This Skill When

  • User asks to "add Sentry to Python" or "setup Sentry" in a Python app
  • User wants error monitoring, tracing, profiling, logging, metrics, or crons in Python
  • User mentions sentry-sdk, sentry_sdk, or Sentry + any Python framework
  • User wants to monitor Django views, Flask routes, FastAPI endpoints, Celery tasks, or scheduled jobs

Note: SDK versions and APIs below reflect Sentry docs at time of writing (sentry-sdk 2.x). Always verify against docs.sentry.io/platforms/python/ before implementing.


Phase 1: Detect

Run these commands to understand the project before making recommendations:

# Check existing Sentry
grep -i sentry requirements.txt pyproject.toml setup.cfg setup.py 2>/dev/null

# Detect web framework
grep -rE "django|flask|fastapi|starlette|aiohttp|tornado|quart|falcon|sanic|bottle" \
  requirements.txt pyproject.toml 2>/dev/null

# Detect task queues
grep -rE "celery|rq|huey|arq|dramatiq" requirements.txt pyproject.toml 2>/dev/null

# Detect logging libraries
grep -E "loguru" requirements.txt pyproject.toml 2>/dev/null

# Detect AI libraries
grep -rE "openai|anthropic|langchain|huggingface|google-genai|pydantic-ai|litellm" \
  requirements.txt pyproject.toml 2>/dev/null

# Detect schedulers / crons
grep -rE "celery|apscheduler|schedule|crontab" requirements.txt pyproject.toml 2>/dev/null

# Check for companion frontend
ls frontend/ web/ client/ ui/ static/ templates/ 2>/dev/null

What to note:

  • Is sentry-sdk already in requirements? If yes, check if sentry_sdk.init() is present — may just need feature config.
  • Which framework? (Determines where to place sentry_sdk.init().)
  • Which task queue? (Celery needs dual-process init; RQ needs a settings file.)
  • AI libraries? (OpenAI, Anthropic, LangChain are auto-instrumented.)
  • Companion frontend? (Triggers Phase 4 cross-link.)

Phase 2: Recommend

Based on what you found, present a concrete proposal. Don't ask open-ended questions — lead with a recommendation:

Always recommended (core coverage):

  • ✅ Error Monitoring — captures unhandled exceptions, supports ExceptionGroup (Python 3.11+)
  • ✅ Logging — Python logging stdlib auto-captured; enhanced if Loguru detected

Recommend when detected:

  • ✅ Tracing — HTTP framework detected (Django/Flask/FastAPI/etc.)
  • ✅ AI Monitoring — OpenAI/Anthropic/LangChain/etc. detected (auto-instrumented, zero config)
  • ⚡ Profiling — production apps where performance matters
  • ⚡ Crons — Celery Beat, APScheduler, or cron patterns detected
  • ⚡ Metrics — business KPIs, SLO tracking

Recommendation matrix:

FeatureRecommend when...Reference
Error MonitoringAlways — non-negotiable baseline${SKILL_ROOT}/references/error-monitoring.md
TracingDjango/Flask/FastAPI/AIOHTTP/etc. detected${SKILL_ROOT}/references/tracing.md
ProfilingProduction + performance-sensitive workload${SKILL_ROOT}/references/profiling.md
LoggingAlways (stdlib); enhanced for Loguru${SKILL_ROOT}/references/logging.md
MetricsBusiness events or SLO tracking needed${SKILL_ROOT}/references/metrics.md
CronsCelery Beat, APScheduler, or cron patterns${SKILL_ROOT}/references/crons.md
AI MonitoringOpenAI/Anthropic/LangChain/etc. detected${SKILL_ROOT}/references/ai-monitoring.md

Propose: "I recommend Error Monitoring + Tracing [+ Logging if applicable]. Want Profiling, Crons, or AI Monitoring too?"


Phase 3: Guide

Install

# Core SDK (always required)
pip install sentry-sdk

# Optional extras (install only what matches detected framework):
pip install "sentry-sdk[django]"
pip install "sentry-sdk[flask]"
pip install "sentry-sdk[fastapi]"
pip install "sentry-sdk[celery]"
pip install "sentry-sdk[aiohttp]"
pip install "sentry-sdk[tornado]"

# Multiple extras:
pip install "sentry-sdk[django,celery]"

Extras are optional — plain sentry-sdk works for all frameworks. Extras install complementary packages.

Quick Start — Recommended Init

Full init enabling the most features with sensible defaults. Place before any app/framework code:

import sentry_sdk

sentry_sdk.init(
    dsn=os.environ["SENTRY_DSN"],
    environment=os.environ.get("SENTRY_ENVIRONMENT", "production"),
    release=os.environ.get("SENTRY_RELEASE"),   # e.g. "myapp@1.0.0"
    send_default_pii=True,

    # Tracing (lower to 0.1–0.2 in high-traffic production)
    traces_sample_rate=1.0,

    # Profiling — continuous, tied to active spans
    profile_session_sample_rate=1.0,
    profile_lifecycle="trace",

    # Structured logs (SDK ≥ 2.35.0)
    enable_logs=True,
)

Where to Initialize Per Framework

FrameworkWhere to call sentry_sdk.init()Notes
DjangoTop of settings.py, before any importsNo middleware needed — Sentry patches Django internally
FlaskBefore app = Flask(__name__)Must precede app creation
FastAPIBefore app = FastAPI()StarletteIntegration + FastApiIntegration auto-enabled together
StarletteBefore app = Starlette(...)Same auto-integration as FastAPI
AIOHTTPModule level, before web.Application()
TornadoModule level, before app setupNo integration class needed
QuartBefore app = Quart(__name__)
FalconModule level, before app = falcon.App()
SanicInside @app.listener("before_server_start")Sanic's lifecycle requires async init
Celery@signals.celeryd_init.connect in worker AND in calling processDual-process init required
RQmysettings.py loaded by worker via rq worker -c mysettings
ARQBoth worker module and enqueuing process

Django example (settings.py):

import sentry_sdk

sentry_sdk.init(
    dsn=os.environ["SENTRY_DSN"],
    send_default_pii=True,
    traces_sample_rate=1.0,
    profile_session_sample_rate=1.0,
    profile_lifecycle="trace",
    enable_logs=True,
)

# rest of Django settings...
INSTALLED_APPS = [...]

FastAPI example (main.py):

import sentry_sdk

sentry_sdk.init(
    dsn=os.environ["SENTRY_DSN"],
    send_default_pii=True,
    traces_sample_rate=1.0,
    profile_session_sample_rate=1.0,
    profile_lifecycle="trace",
    enable_logs=True,
)

from fastapi import FastAPI
app = FastAPI()

Auto-Enabled vs Explicit Integrations

Most integrations activate automatically when their package is installed — no integrations=[...] needed:

Auto-enabledExplicit required
Django, Flask, FastAPI, Starlette, AIOHTTP, Tornado, Quart, Falcon, Sanic, BottleDramatiqIntegration
Celery, RQ, Huey, ARQGRPCIntegration
SQLAlchemy, Redis, asyncpg, pymongoStrawberryIntegration
Requests, HTTPX, aiohttp-clientAsyncioIntegration
OpenAI, Anthropic, LangChain, Pydantic AI, MCPOpenTelemetryIntegration
Python logging, LoguruWSGIIntegration / ASGIIntegration

For Each Agreed Feature

Walk through features one at a time. Load the reference, follow its steps, verify before moving on:

FeatureReference fileLoad when...
Error Monitoring${SKILL_ROOT}/references/error-monitoring.mdAlways (baseline)
Tracing${SKILL_ROOT}/references/tracing.mdHTTP handlers / distributed tracing
Profiling${SKILL_ROOT}/references/profiling.mdPerformance-sensitive production
Logging${SKILL_ROOT}/references/logging.mdAlways; enhanced for Loguru
Metrics${SKILL_ROOT}/references/metrics.mdBusiness KPIs / SLO tracking
Crons${SKILL_ROOT}/references/crons.mdScheduler / cron patterns detected
AI Monitoring${SKILL_ROOT}/references/ai-monitoring.mdAI library detected

For each feature: Read ${SKILL_ROOT}/references/<feature>.md, follow steps exactly, verify it works.


Configuration Reference

Key sentry_sdk.init() Options

OptionTypeDefaultPurpose
dsnstrNoneSDK disabled if empty; env: SENTRY_DSN
environmentstr"production"e.g., "staging"; env: SENTRY_ENVIRONMENT
releasestrNonee.g., "myapp@1.0.0"; env: SENTRY_RELEASE
send_default_piiboolFalseInclude IP, headers, cookies, auth user
traces_sample_ratefloatNoneTransaction sample rate; None disables tracing
traces_samplerCallableNoneCustom per-transaction sampling (overrides rate)
profile_session_sample_ratefloatNoneContinuous profiling session rate
profile_lifecyclestr"manual""trace" = auto-start profiler with spans
profiles_sample_ratefloatNoneTransaction-based profiling rate
enable_logsboolFalseSend logs to Sentry (SDK ≥ 2.35.0)
sample_ratefloat1.0Error event sample rate
attach_stacktraceboolFalseStack traces on capture_message()
max_breadcrumbsint100Max breadcrumbs per event
debugboolFalseVerbose SDK debug output
before_sendCallableNoneHook to mutate/drop error events
before_send_transactionCallableNoneHook to mutate/drop transaction events
ignore_errorslist[]Exception types or regex patterns to suppress
auto_enabling_integrationsboolTrueSet False to disable all auto-detection

Environment Variables

VariableMaps toNotes
SENTRY_DSNdsn
SENTRY_RELEASEreleaseAlso auto-detected from git SHA, Heroku, CircleCI, CodeBuild, GAE
SENTRY_ENVIRONMENTenvironment
SENTRY_DEBUGdebug

Verification

Test that Sentry is receiving events:

# Trigger a real error event — check dashboard within seconds
division_by_zero = 1 / 0

Or for a non-crashing check:

sentry_sdk.capture_message("Sentry Python SDK test")

If nothing appears:

  1. Set debug=True in sentry_sdk.init() — prints SDK internals to stdout
  2. Verify the DSN is correct
  3. Check SENTRY_DSN env var is set in the running process
  4. For Celery/RQ: ensure init runs in the worker process, not just the calling process

Phase 4: Cross-Link

After completing Python setup, check for a companion frontend missing Sentry:

ls frontend/ web/ client/ ui/ 2>/dev/null
cat frontend/package.json web/package.json client/package.json 2>/dev/null \
  | grep -E '"react"|"svelte"|"vue"|"next"|"nuxt"'

If a frontend exists without Sentry, suggest the matching skill:

Frontend detectedSuggest skill
React / Next.jssentry-react-sdk
Svelte / SvelteKitsentry-svelte-sdk
Vue / NuxtUse @sentry/vue — see docs.sentry.io/platforms/javascript/guides/vue/
Other JS/TSsentry-react-sdk (covers generic browser JS patterns)

Troubleshooting

IssueSolution
Events not appearingSet debug=True, verify DSN, check env vars in the running process
Malformed DSN errorFormat: https://<key>@o<org>.ingest.sentry.io/<project>
Django exceptions not capturedEnsure sentry_sdk.init() is at the top of settings.py before other imports
Flask exceptions not capturedInit must happen before app = Flask(__name__)
FastAPI exceptions not capturedInit before app = FastAPI(); both StarletteIntegration and FastApiIntegration auto-enabled
Celery task errors not capturedMust call sentry_sdk.init() in the worker process via celeryd_init signal
Sanic init not workingInit must be inside @app.listener("before_server_start"), not module level
uWSGI not capturingAdd --enable-threads --py-call-uwsgi-fork-hooks to uWSGI command
No traces appearingVerify traces_sample_rate is set (not None); check that the integration is auto-enabled
Profiling not startingRequires traces_sample_rate > 0 + either profile_session_sample_rate or profiles_sample_rate
enable_logs not workingRequires SDK ≥ 2.35.0; for direct structured logs use sentry_sdk.logger; for stdlib bridging use LoggingIntegration(sentry_logs_level=...)
Too many transactionsLower traces_sample_rate or use traces_sampler to drop health checks
Cross-request data leakingDon't use get_global_scope() for per-request data — use get_isolation_scope()
RQ worker not reportingPass --sentry-dsn="" to disable RQ's own Sentry shortcut; init via settings file instead

FAQ

What does the sentry-python-sdk skill do?

Full Sentry SDK setup for Python. Use when asked to "add Sentry to Python", "install sentry-sdk", "setup Sentry in Python", or configure error monitoring, tracing, profiling, logging, metrics, crons, or AI monitoring for Python applications. Supports Django, Flask, FastAPI, Celery, Starlette, AIOHTTP, Tornado, and more.

How do I install sentry-python-sdk?

Run npx skills add https://github.com/getsentry/sentry-agent-skills --skill sentry-python-sdk in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/sentry-python-sdk/ (personal) or .claude/skills/sentry-python-sdk/ (project).

Which AI agents can use sentry-python-sdk?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is sentry-python-sdk safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains sentry-python-sdk?

It is published by getsentry in getsentry/sentry-agent-skills, and it is an official skill from the maker of the technology it covers. It has 378 recorded installs.

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