Provides tools to interact with Sentry's API, enabling retrieval of detailed issue information, stacktraces, and distributed tracing data, as well as searching for specific events within issues.
A fast, lightweight MCP server for Sentry, written in Rust.
Compared to the official Node.js server:
Memory: 10x less RAM usage
Startup: instant cold start
Disk: single binary, no runtime dependencies
Tokens: fewer tools = smaller tool list in context
Related MCP server: cursor-rust-tools
This MCP server provides tools to interact with Sentry's API:
get_issue_details - Retrieve detailed information about a Sentry issue including metadata, tags, stacktraces, and optionally a specific event
get_trace_details - Retrieve trace details including span tree and timing information for distributed tracing analysis
search_issue_events - Search events within an issue using Sentry's query syntax
From crates.io:
cargo install sentry-mcpFrom GitHub:
cargo install --git https://github.com/utapyngo/sentry-mcp-rs.gitOr with mise:
mise use -g github:utapyngo/sentry-mcp-rsThe binary will be installed as sentry-mcp.
Required environment variables:
SENTRY_AUTH_TOKEN - Your Sentry API authentication token
SENTRY_HOST - Your Sentry instance hostname (e.g., sentry.io)
Optional:
SOCKS_PROXY - SOCKS5 proxy URL (e.g., socks5://127.0.0.1:1080)
HTTPS_PROXY - HTTPS proxy URL
Add to your MCP client configuration:
{
"mcpServers": {
"sentry": {
"command": "sentry-mcp",
"env": {
"SENTRY_AUTH_TOKEN": "your_token_here",
"SENTRY_HOST": "sentry.io"
}
}
}
}Or without installation using mise:
{
"mcpServers": {
"sentry": {
"command": "mise",
"args": ["x", "github:utapyngo/sentry-mcp-rs", "--", "sentry-mcp"],
"env": {
"SENTRY_AUTH_TOKEN": "your_token_here",
"SENTRY_HOST": "sentry.io"
}
}
}
}Clone the repository and create a .env file:
git clone https://github.com/utapyngo/sentry-mcp-rs.git
cd sentry-mcp-rs
cp .env.example .env
# Edit .env with your credentialsBuild and test with MCP Inspector:
cargo build --release
npx @modelcontextprotocol/inspector ./run.shOr configure MCP client to use the script:
{
"mcpServers": {
"sentry": {
"command": "/path/to/sentry-mcp-rs/run.sh"
}
}
}Retrieve detailed information about a specific Sentry issue.
Parameters:
issue_url - Full Sentry issue URL (alternative to the parameters below)
organization_slug - Organization slug (required if issue_url not provided)
issue_id - Issue ID like PROJECT-123 or numeric ID (required if issue_url not provided)
event_id - Specific event ID to fetch instead of latest (optional)
Retrieve trace details for distributed tracing analysis.
Parameters:
organization_slug - Organization slug
trace_id - 32-character hex trace ID
Search events within an issue using Sentry's query syntax.
Parameters:
organization_slug - Organization slug
issue_id - Issue ID (e.g., PROJECT-123)
query - Optional Sentry search query
limit - Maximum events to return (default: 10, max: 100)
sort - Sort order: newest (default) or oldest
Retrieve detailed information about a specific Sentry issue including metadata, tags, and optionally an event. Accepts either an issueUrl OR (organizationSlug + issueId).
| Name | Required | Description | Default |
|---|---|---|---|
| event_id | No | Specific event ID to fetch instead of latest | |
| issue_id | No | Issue ID like 'PROJECT-123' or numeric ID (required if issue_url not provided) | |
| issue_url | No | Full Sentry issue URL | |
| organization_slug | No | Organization slug (required if issue_url not provided) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses the tool is read-only (retrieve), but with no annotations, lacks details on error handling, authentication needs, or what happens if the issue does not exist. The description is adequate but not comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single, well-structured sentence that immediately states purpose and key usage information. No unnecessary words; front-loaded with verb and resource.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Tool has no output schema and no annotations, so description must compensate. It covers identification methods and high-level contents, but lacks details on return structure, pagination, or error scenarios, leaving some gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has 100% description coverage, providing clear parameter roles. The description adds the constraint of mutual exclusivity between issue_url and organizationSlug+issueId, offering some extra value but not enough to exceed baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool retrieves detailed issue info from Sentry, listing metadata, tags, and optional event. It distinguishes the tool from siblings by focusing on a single issue, though not explicitly contrasting with get_trace_details or search_issue_events.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Implicitly describes when to use via the two identification modes, but lacks explicit guidance on when to choose this tool over siblings, such as searching events within an issue or getting trace details.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Retrieve trace details including span tree and timing information. Useful for analyzing distributed system performance.
| Name | Required | Description | Default |
|---|---|---|---|
| organization_slug | Yes | Organization slug | |
| trace_id | Yes | Trace ID (32-character hex string) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden for behavioral disclosure. 'Retrieve' implies a read-only operation, and the description lists the outputs (span tree, timing information), which is sufficient for a simple retrieval tool. However, it does not explicitly state that the operation is idempotent or has no side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is only two sentences, with the first sentence clearly stating the action and outputs. There is no redundant information, and every sentence adds value. It is front-loaded and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the low complexity (2 simple params, no output schema, no nested objects), the description provides adequate context. It explains the purpose and output (span tree, timing), which is sufficient for an agent to invoke the tool correctly. Could include more details about the span tree structure, but not necessary.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% (both parameters have descriptions in the input schema). The description adds no additional meaning beyond the schema, as 'organization_slug' and 'trace_id' are already well-defined. Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Retrieve'), the specific resource ('trace details'), and key outputs ('span tree and timing information'). It also differentiates from sibling tools (get_issue_details, search_issue_events) by focusing on distributed system performance analysis.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions the tool is 'useful for analyzing distributed system performance,' which gives context for when to use it. However, it lacks explicit guidance on when not to use it or when to prefer alternative tools, though the differentiation from sibling tools is implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Search events for a specific issue using a query string. Returns matching events with their details.
| Name | Required | Description | Default |
|---|---|---|---|
| issue_id | Yes | Issue ID like 'PROJECT-123' or numeric ID | |
| limit | No | Maximum number of events to return (default: 10, max: 100) | |
| organization_slug | Yes | Organization slug | |
| query | No | Sentry search query. Syntax: key:value pairs with optional raw text. Operators: > < >= <= for numbers, ! for negation, * for wildcard, OR/AND for logic. Event properties: environment, release, platform, message, user.id, user.email, device.family, browser.name, os.name, server_name, transaction. Examples: 'server_name:web-1', 'environment:production', '!user.email:*@test.com', 'browser.name:Chrome OR browser.name:Firefox' | |
| sort | No | Sort order: 'newest' (default) or 'oldest' |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions 'search' and 'returns matching events' but does not disclose if the operation is read-only, what side effects exist, required permissions, rate limits, or what happens on empty results. The description is minimal on behavioral traits beyond the core action.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, very concise with no extraneous information. It front-loads the key action and outcome. However, it could be more structured (e.g., bullets for when to use) but given its brevity, it is efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (5 parameters, no output schema, 2 siblings), the description provides the core purpose but lacks details about return format, pagination, error cases, or common event properties. It is adequate for a straightforward search tool but could be more informative for agents needing to handle edge cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with detailed descriptions for each parameter, especially 'query' which provides syntax, operators, and examples. The description only restates 'using a query string', adding little beyond the schema. Since the schema already documents parameters well, a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states it 'Search events for a specific issue using a query string. Returns matching events with their details.' It clearly identifies the action (search), the resource (events for a specific issue), and the result (matching events with details). It also distinguishes itself from sibling tools 'get_issue_details' and 'get_trace_details' which focus on issue or trace details, not events.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives a general purpose but does not explicitly state when to use this tool versus alternatives. It implies usage when events are needed rather than issue details, but lacks guidance on prerequisites, when-not-to-use, or comparison with sibling tools. The schema descriptions provide some context for parameter usage but not for tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
v0.1.0get_issue_detailsget_trace_detailssearch_issue_eventsScored across 3 tools
Each tool targets a distinct operation: issue details, trace details, and event search. There is no overlap or ambiguity between them.
All tools follow a consistent verb_noun pattern using snake_case, e.g., get_issue_details, get_trace_details, search_issue_events.
Three tools is on the lower side but still reasonable for a focused Sentry server covering core issue and trace functionality.
The set lacks essential CRUD operations like listing issues, updating issue status, or resolving issues, leaving significant gaps for a comprehensive Sentry workflow.
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