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Overview

The Sentry integration pulls production error data into PR reviews. When Nectr reviews a PR, it queries the Sentry MCP server for recent errors related to the files being changed. This helps reviewers catch regressions before merging. Example: A PR modifies app/services/auth.py. Nectr fetches Sentry errors where culprit contains auth.py and includes them in the review context:
  • “OAuth token validation failed (seen 127 times in the last 24h)”
  • “Redis connection timeout in session refresh (seen 43 times)“

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How It Works

Sentry integration uses the Model Context Protocol (MCP) — Nectr acts as an MCP client and calls a Sentry MCP server to fetch errors.

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Graceful Degradation

If SENTRY_MCP_URL is not set or the Sentry MCP server is offline:
  • Nectr logs an info message: "SENTRY_MCP_URL not configured — skipping Sentry error fetch"
  • Returns an empty list []
  • Review continues without Sentry context

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Prerequisites

  1. Sentry Account (free or paid plan)
  2. Sentry Auth Token (sentry.io/settings/account/api/auth-tokens/)
  3. Sentry MCP Server (self-hosted or cloud-deployed)

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Setup Guide

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1. Generate a Sentry Auth Token

1

Navigate to Sentry API Settings

Go to sentry.io/settings/account/api/auth-tokens/
2

Create New Token

  • Name: Nectr MCP Server
  • Scopes: event:read, project:read, org:read
3

Copy Token

Save the token immediately — you won’t be able to see it again.

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2. Deploy a Sentry MCP Server

You need an external MCP server that implements the search_errors tool. This server bridges Sentry’s REST API and the MCP protocol.

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3. Set Environment Variables

Add the following to Nectr’s .env:
.env
# Sentry MCP server URL
SENTRY_MCP_URL=http://sentry-mcp-server:8002

# Sentry auth token (passed as Authorization header)
SENTRY_AUTH_TOKEN=sntrys_...

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4. Restart Nectr

docker compose restart backend
# or
uvicorn app.main:app --reload

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Usage

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Automatic Error Fetching

When a PR is opened, Nectr automatically:
  1. Extracts changed files from the PR diff
  2. Calls Sentry MCP server for each file: search_errors(project, filename)
  3. Includes error context in the AI prompt
Example: 
from app.mcp.client import mcp_client

errors = await mcp_client.get_sentry_errors(
    project="backend",
    filename="app/services/auth.py"
)
# Returns: [
#   {"id": "123456", "title": "Redis timeout", "culprit": "auth.py:42", "count": 127, "last_seen": "2026-03-10T10:00:00Z"},
#   {"id": "123457", "title": "OAuth validation error", "culprit": "auth.py:78", "count": 43, "last_seen": "2026-03-10T09:30:00Z"},
# ]

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Manual Testing

Test the Sentry MCP server directly: 
curl -X POST http://sentry-mcp-server:8002/ \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer sntrys_..." \
  -d '{
    "jsonrpc": "2.0",
    "id": 1,
    "method": "tools/call",
    "params": {
      "name": "search_errors",
      "arguments": {"project": "backend", "filename": "auth.py"}
    }
  }'
Expected Response: 
{
  "result": {
    "content": [
      {
        "type": "text",
        "text": "[{\"id\": \"123456\", \"title\": \"Redis timeout\", \"culprit\": \"auth.py:42\", \"count\": 127}]"
      }
    ]
  }
}

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Implementation Details

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MCPClientManager

File: app/mcp/client.py:70 
async def get_sentry_errors(self, project: str, filename: str) -> list[dict]:
    """Get recent Sentry errors related to a file being reviewed.

    Args:
        project:  Sentry project slug (e.g. "backend").
        filename: File path from the PR diff to filter errors by.

    Returns:
        List of error dicts: {id, title, culprit, count, last_seen}.
        Empty list if Sentry MCP is not configured or the call fails.
    """
    if not settings.SENTRY_MCP_URL:
        logger.info(
            "SENTRY_MCP_URL not configured — skipping Sentry error fetch "
            "(set SENTRY_MCP_URL + SENTRY_AUTH_TOKEN to enable)"
        )
        return []

    return await self.query_mcp_server(
        server_url=settings.SENTRY_MCP_URL,
        tool_name="search_errors",
        args={"project": project, "filename": filename},
        auth_token=settings.SENTRY_AUTH_TOKEN,
    )

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MCP Request Format

File: app/mcp/client.py:116 
payload = {
    "jsonrpc": "2.0",
    "id": 1,
    "method": "tools/call",
    "params": {
        "name": "search_errors",
        "arguments": {"project": "backend", "filename": "auth.py"}
    },
}
headers = {
    "Content-Type": "application/json",
    "Authorization": f"Bearer {settings.SENTRY_AUTH_TOKEN}"
}

response = await client.post(
    f"{settings.SENTRY_MCP_URL}/",
    json=payload,
    headers=headers,
)

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Configuration Reference

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SENTRY_MCP_URL
string
required
Base URL of the Sentry MCP server (e.g., http://sentry-mcp-server:8002)
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SENTRY_AUTH_TOKEN
string
required
Sentry auth token for API access. Generate at sentry.io/settings/account/api/auth-tokens/.Required scopes: event:read, project:read, org:read

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Troubleshooting

Cause: Sentry MCP server is not running or SENTRY_MCP_URL is incorrect.Fix:
  • Test the MCP server directly: curl http://sentry-mcp-server:8002/
  • Check logs: docker logs sentry-mcp-server
  • Verify SENTRY_MCP_URL is set in Nectr’s .env
Cause: SENTRY_AUTH_TOKEN is missing, invalid, or lacks required scopes.Fix:
Cause: Sentry API is slow or MCP server is overloaded.Fix:
  • Increase timeout: Edit _MCP_TIMEOUT in app/mcp/client.py (default: 10s)
  • Add caching to the MCP server (cache error queries for 60s)
  • Filter errors by date range (last 7 days instead of all-time)
Cause: culprit matching is too broad (e.g., “auth.py” matches “oauth.py”).Fix:
  • Use full file paths in MCP server: app/services/auth.py instead of auth.py
  • Filter errors by first_seen or last_seen date (only recent errors)

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Next Steps

MCP Protocol

Understand how MCP connects Nectr with Sentry

Slack Integration

Fetch relevant channel messages as review context

Environment Variables

Full configuration reference

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