# Sentry MCP - AI Error Monitoring for Agents (`red.cars/sentry-mcp`) Actor 219 tools for AI agents that fix bugs. Wraps the Sentry PP CLI as an MCP server with PPE billing. - **URL**: https://apify.com/red.cars/sentry-mcp.md - **Developed by:** [AutomateLab](https://apify.com/red.cars) (community) - **Categories:** MCP servers, AI - **Stats:** 1 total users, 1 monthly users, 0.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing Pay per event + usage This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Sentry MCP Actor **219 tools for AI agents that fix bugs.** This Apify Actor wraps the Sentry PP CLI as an MCP server, enabling AI agents to monitor, investigate, and resolve errors programmatically. ### What does Sentry MCP do? Sentry MCP provides **comprehensive error monitoring and issue management** through 219 tools. AI agents can use these tools to: - **List and search events** from Sentry projects - **Manage issues** (create, update, assign, resolve) - **Query releases** and deployment data - **Access organization and team data** across your Sentry workspace - **Get detailed event context** including stack traces, breadcrumbs, and context variables This Actor is designed for AI agent workflows — your agent can call Sentry tools directly to understand errors, track down bugs, and get the context needed to fix issues. ### Why use Sentry MCP? - **Agent-native error monitoring** — give your AI agents direct access to Sentry's error data - **Automatic PPE billing** — pay-per-event pricing via Apify's platform - **Standby MCP server** — serves the MCP protocol over HTTP for flexible integration - **Combined with Apify Actors** — schedule, orchestrate, and monitor your error monitoring workflows ### How to use Sentry MCP #### Method 1: Direct tool call via API ```bash curl -X POST https://api.apify.com/v2/acts/YOUR-USER-NAME~sentry-mcp/runs \ -H "Content-Type: application/json" \ -d '{ "tool": "issues_list", "args": { "project": "my-project", "first": 10 } }' ```` #### Method 2: MCP Protocol (for AI agents) Connect to the MCP endpoint at `https://api.apify.com/v2/acts/YOUR-USER-NAME~sentry-mcp/mcp` using any MCP-compatible client. The Actor serves the MCP JSON-RPC protocol in standby mode. #### Available tools (sample) | Tool | Description | |------|-------------| | `events_list` | List events for a project | | `issues_list` | List issues with filters | | `releases_list` | List all releases | | `projects_list` | List all projects | | `teams_list` | List organization teams | | `org_list` | List organizations | | `issue_activity` | Get issue activity stream | | `events_aggregate` | Aggregate events | | `project_stats` | Project-level statistics | #### Authentication Set the `SENTRY_AUTH_TOKEN` secret in the Apify Console. This should be a Sentry API token with appropriate scopes for the tools you're using. ### Input | Field | Type | Description | |-------|------|-------------| | `tool` | string | Tool name to call (e.g., `events_list`, `issues_list`) | | `args` | object | Tool arguments as key-value pairs | Example input: ```json { "tool": "events_list", "args": { "project": "my-backend-service", "first": 10, "query": "is:unresolved" } } ``` ### Output The Actor outputs results to the default dataset. Example: ```json { "result": { "data": [ { "id": "1234567890", "type": "error", "message": "TypeError: Cannot read property 'foo' of undefined", "culprit": "src/handlers/user.js in processUser", "project": "my-backend-service", "count": 42, "userCount": 5 } ], "meta": { "pagination": { "next": "https://sentry.io/api/0/projects/..." } } }, "tool": "events_list", "timestamp": "2026-05-09T20:00:00.000Z" } ``` You can download the output dataset in JSON, CSV, HTML, or Excel formats. ### Pricing / Cost estimation This Actor uses **Pay-Per-Event (PPE)** pricing: | Event Type | Price | |------------|-------| | `list_tools` | $0.00 | | `sentry_events_list` | $0.10 | | `sentry_issues_list` | $0.08 | | `sentry_releases_list` | $0.05 | | `sentry_projects_list` | $0.05 | | Other tools | $0.03 - $0.10 | Set pricing via the Apify Console or API. Default events (actor start, etc.) are free. ### Tips and advanced options - **Batch processing**: Run the Actor on a schedule to process events in batches - **Filter events**: Use `query` parameter with Sentry search syntax (e.g., `is:unresolved level:error`) - **Pagination**: Use cursor-based pagination via `cursor` parameter in tool args - **Authentication scopes**: Ensure your Sentry token has `event:read`, `project:read`, `org:read` as needed ### FAQ, disclaimers, and support **Rate limits**: Sentry API rate limits apply. Build in retry logic for production use. **Authentication**: Your Sentry token is stored as an Apify secret and never logged. **Known limitations**: - Some tools require specific Sentry plan tiers - Events older than 90 days may not be available depending on your plan For issues or feature requests, open an issue at the GitHub repository or contact support. *** Built on [Apify](https://apify.com) — the platform for web scraping, data extraction, and browser automation. # Actor input Schema ## `tool` (type: `string`): Sentry tool to call (e.g. events\_list, issues\_list, releases\_list) ## `args` (type: `object`): Tool arguments as key-value pairs ## Actor input object example ```json { "tool": "events_list", "args": { "project": "my-project", "first": 10 } } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = {}; // Run the Actor and wait for it to finish const run = await client.actor("red.cars/sentry-mcp").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = {} # Run the Actor and wait for it to finish run = client.actor("red.cars/sentry-mcp").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{}' | apify call red.cars/sentry-mcp --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=red.cars/sentry-mcp", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Sentry MCP - AI Error Monitoring for Agents", "description": "219 tools for AI agents that fix bugs. Wraps the Sentry PP CLI as an MCP server with PPE billing.", "version": "1.0", "x-build-id": "4SmsFBoPzNWEmSerf" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/red.cars~sentry-mcp/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-red.cars-sentry-mcp", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/red.cars~sentry-mcp/runs": { "post": { "operationId": "runs-sync-red.cars-sentry-mcp", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/red.cars~sentry-mcp/run-sync": { "post": { "operationId": "run-sync-red.cars-sentry-mcp", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "tool" ], "properties": { "tool": { "title": "Sentry Tool", "type": "string", "description": "Sentry tool to call (e.g. events_list, issues_list, releases_list)", "default": "events_list" }, "args": { "title": "Tool Arguments", "type": "object", "description": "Tool arguments as key-value pairs" } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```