Sentry MCP Server
OfficialThe Sentry MCP Server allows AI assistants to interact with Sentry's API to manage and monitor application performance through these capabilities:
List accessible Sentry projects with details about slugs, IDs, status, and organization
Retrieve and analyze issues using short IDs or URLs
View specific error events and their metadata
List error events in projects to identify frequency patterns
Create new Sentry projects
Monitor issue status, severity, and frequency
List and analyze user session replays
Set up Sentry for a project with DSN and instructions
Search for errors occurring in specific files
Verified to work with Codeium Windsurf, enabling integration between Sentry error tracking capabilities and Codeium's development environment.
Provides tools to interact with the Sentry API, allowing retrieval and analysis of error data, management of projects, monitoring of application performance, and handling of issues and events.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Sentry MCP Serverlist recent issues in the 'my-org' organization for project 'web-app'"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Note - This has largely been superceded by the Sentry Remote-MCP Server which supports a lot more capabilities (auth, better tooling, etc...). This one exists for educational purposes as a standalone MCP server; but in all likelihood you'll want to use the remote. You can see it live at https://mcp.sentry.dev
Sentry MCP Server
A Model Context Protocol (MCP) server for interacting with Sentry. This MCP server provides tools to interact with the Sentry API, allowing AI assistants to retrieve and analyze error data, manage projects, and monitor application performance.
Requirements
Node.js (v14 or higher)
npm or yarn
Sentry account with API access
Sentry authentication token with appropriate permissions
Related MCP server: Sentry MCP Server
Setup
Install dependencies:
npm install
Using this within an IDE
This MCP has been verified to work against Cursor, Codeium Windsurf, and Claude Desktop.
Using with Claude
To use this MCP server with Claude, add the following configuration to your Claude settings:
{
"mcpServers": {
"sentry": {
"command": "npx",
"args": ["ts-node", "/Users/<your-user-directory>/sentry-mcp-ts/index.ts"],
"env": {
"SENTRY_AUTH": "<YOUR_AUTH_TOKEN>"
}
}
}
}Update with your directory path in the
argsfield.Replace
<YOUR_AUTH_TOKEN>with your Sentry authentication token.
Available Tools
list_projects
Lists all accessible Sentry projects for a given organization.
Parameters:
organization_slug(string, required): The slug of the organization to list projects fromview(string, optional): View type, either "summary" or "detailed" (default: "detailed")format(string, optional): Output format, either "plain" or "markdown" (default: "markdown")
resolve_short_id
Retrieves details about an issue using its short ID.
Parameters:
organization_slug(string, required): The slug of the organization the issue belongs toshort_id(string, required): The short ID of the issue to resolve (e.g., PROJECT-123)format(string, optional): Output format, either "plain" or "markdown" (default: "markdown")
get_sentry_event
Retrieves and analyzes a specific Sentry event from an issue.
Parameters:
issue_id_or_url(string, required): Either a full Sentry issue URL or just the numeric issue IDevent_id(string, required): The specific event ID to retrieveview(string, optional): View type, either "summary" or "detailed" (default: "detailed")format(string, optional): Output format, either "plain" or "markdown" (default: "markdown")
list_error_events_in_project
Lists error events from a specific Sentry project.
Parameters:
organization_slug(string, required): The slug of the organization the project belongs toproject_slug(string, required): The slug of the project to list events fromview(string, optional): View type, either "summary" or "detailed" (default: "detailed")format(string, optional): Output format, either "plain" or "markdown" (default: "markdown")
create_project
Creates a new project in Sentry and retrieves its client keys.
Parameters:
organization_slug(string, required): The slug of the organization to create the project inteam_slug(string, required): The slug of the team to assign the project toname(string, required): The name of the new projectplatform(string, optional): The platform for the new projectview(string, optional): View type, either "summary" or "detailed" (default: "detailed")format(string, optional): Output format, either "plain" or "markdown" (default: "markdown")
list_project_issues
Lists issues from a specific Sentry project.
Parameters:
organization_slug(string, required): The slug of the organization the project belongs toproject_slug(string, required): The slug of the project to list issues fromview(string, optional): View type, either "summary" or "detailed" (default: "detailed")format(string, optional): Output format, either "plain" or "markdown" (default: "markdown")
list_issue_events
Lists events for a specific Sentry issue.
Parameters:
organization_slug(string, required): The slug of the organization the issue belongs toissue_id(string, required): The ID of the issue to list events fromview(string, optional): View type, either "summary" or "detailed" (default: "detailed")format(string, optional): Output format, either "plain" or "markdown" (default: "markdown")
get_sentry_issue
Retrieves and analyzes a Sentry issue.
Parameters:
issue_id_or_url(string, required): Either a full Sentry issue URL or just the numeric issue IDview(string, optional): View type, either "summary" or "detailed" (default: "detailed")format(string, optional): Output format, either "plain" or "markdown" (default: "markdown")
list_organization_replays
Lists replays from a specific Sentry organization.
Parameters:
organization_slug(string, required): The slug of the organization to list replays fromproject_ids(string[], optional): List of project IDs to filter replays byenvironment(string, optional): Environment to filter replays bystats_period(string, optional): Time period for stats (e.g., "24h", "7d")start(string, optional): Start date for filtering replaysend(string, optional): End date for filtering replayssort(string, optional): Field to sort replays byquery(string, optional): Search query to filter replaysper_page(number, optional): Number of replays per pagecursor(string, optional): Cursor for paginationview(string, optional): View type, either "summary" or "detailed" (default: "detailed")format(string, optional): Output format, either "plain" or "markdown" (default: "markdown")
Running the Server
npx ts-node index.tsAuthentication
This tool requires a Sentry authentication token with appropriate permissions to access the Sentry API. You can generate a token in your Sentry account settings under Settings -> User Settings -> Auth Tokens.
Available Tools
11 toolscreate_projectB
Create a new project in Sentry. Track deployments, releases, and health metrics.
| Name | Required | Description | Default |
|---|---|---|---|
| organization_slug | Yes | The slug of the organization to create the project in | |
| team_slug | Yes | The slug of the team to associate the project with | |
| name | Yes | The name of the project to create | |
| platform | No | The platform for the project (e.g., python, javascript, etc.) | |
| view | No | View type (default: detailed) | detailed |
| format | No | Output format (default: markdown) | markdown |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states 'Create a new project' which implies a write/mutation operation, but doesn't mention permissions, side effects, error handling, or response format. The tracking context is helpful but insufficient for a mutation tool.
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, efficient sentence that front-loads the core purpose ('Create a new project in Sentry') and adds useful context about tracking. Every word earns its place with no redundancy or waste.
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?
For a mutation tool with 6 parameters, no annotations, and no output schema, the description is minimally adequate. It covers the basic purpose but lacks behavioral details, usage context, and output information that would be needed for full completeness.
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%, so the schema fully documents all 6 parameters. The description adds no parameter-specific information beyond what's in the schema, maintaining the baseline score of 3 for adequate coverage without extra value.
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 ('Create a new project') and resource ('in Sentry'), with additional context about what the project will track. It doesn't explicitly differentiate from sibling tools like 'list_projects' or 'setup_sentry', but the verb 'Create' makes the purpose unambiguous.
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 provides no guidance on when to use this tool versus alternatives like 'list_projects' or 'setup_sentry'. It mentions what the project tracks but doesn't specify prerequisites, conditions, or exclusions for usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_sentry_eventB
Retrieve a specific Sentry event from an issue. Requires issue ID/URL and event ID.
| Name | Required | Description | Default |
|---|---|---|---|
| issue_id_or_url | Yes | Either a full Sentry issue URL or just the numeric issue ID | |
| event_id | Yes | The specific event ID to retrieve | |
| organization_slug | Yes | The slug of the organization the issue belongs to | |
| view | No | View type (default: detailed) | detailed |
| format | No | Output format (default: markdown) | markdown |
TDQS
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 required parameters but doesn't disclose behavioral traits such as authentication needs, rate limits, error handling, or what the retrieved event includes (e.g., metadata, stack traces). For a retrieval tool with no annotation coverage, this is a significant gap in transparency.
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 appropriately sized and front-loaded, consisting of two concise sentences that state the purpose and prerequisites without waste. Every sentence earns its place by providing essential information, making it efficient and well-structured.
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 no annotations and no output schema, the description is incomplete for a tool with 5 parameters and retrieval functionality. It lacks details on behavioral aspects (e.g., permissions, response format) and doesn't compensate for the missing output schema, leaving gaps in understanding how to interpret results.
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%, so the schema already documents all parameters thoroughly. The description adds minimal value by naming 'issue ID/URL and event ID' as required, but doesn't provide additional context beyond what's in the schema (e.g., explaining how to derive organization_slug). Baseline 3 is appropriate as the schema does the heavy lifting.
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 tool's purpose: 'Retrieve a specific Sentry event from an issue.' It specifies the verb ('retrieve') and resource ('Sentry event'), and distinguishes it from siblings like 'list_issue_events' by focusing on a single event. However, it doesn't explicitly differentiate from 'get_sentry_issue' beyond the resource type, which slightly limits clarity.
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 implies usage by stating 'Requires issue ID/URL and event ID,' which suggests prerequisites but doesn't explicitly guide when to use this tool versus alternatives like 'list_issue_events' for multiple events or 'get_sentry_issue' for issue-level data. No exclusions or specific contexts are provided, leaving usage somewhat inferred.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_sentry_issueC
Retrieve and analyze a Sentry issue. Accepts issue URL or ID.
| Name | Required | Description | Default |
|---|---|---|---|
| issue_id_or_url | Yes | Either a full Sentry issue URL or just the numeric issue ID | |
| organization_slug | Yes | The slug of the organization the issue belongs to | |
| view | No | View type (default: detailed) | detailed |
| format | No | Output format (default: markdown) | markdown |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but offers minimal behavioral insight. It mentions 'analyze' which suggests some processing beyond simple retrieval, but doesn't clarify what analysis entails, authentication requirements, rate limits, or response format. The description doesn't contradict annotations (none exist), but fails to disclose key operational traits.
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 extremely concise at just two sentences, with no wasted words. It's front-loaded with the core purpose and efficiently states parameter acceptance. Every sentence serves a clear purpose without redundancy.
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?
For a tool with 4 parameters, no annotations, and no output schema, the description is insufficient. It doesn't explain what 'analyze' means in practice, what the tool returns, or how it differs from sibling tools. The lack of behavioral context and output information leaves significant gaps for an agent to understand this tool's full functionality.
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%, providing detailed parameter documentation. The description adds marginal value by mentioning 'Accepts issue URL or ID' which aligns with the 'issue_id_or_url' parameter, but doesn't elaborate on parameter interactions or provide context beyond what's in the schema. Baseline 3 is appropriate given comprehensive schema coverage.
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 and analyze') and resource ('a Sentry issue'), making the purpose understandable. It distinguishes from siblings like 'get_sentry_event' by focusing on issues rather than events, but doesn't explicitly contrast with 'list_project_issues' or 'resolve_short_id', which also handle issues.
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 provides no guidance on when to use this tool versus alternatives. It doesn't mention when to choose 'get_sentry_issue' over 'get_sentry_event' for related data, or how it differs from 'list_project_issues' for browsing multiple issues. No context about prerequisites or typical use cases is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_error_events_in_projectC
List error events from a specific Sentry project. View recent errors, frequency patterns, and occurrence timestamps.
| Name | Required | Description | Default |
|---|---|---|---|
| organization_slug | Yes | The slug of the organization the project belongs to | |
| project_slug | Yes | The slug of the project to list events from | |
| view | No | View type (default: detailed) | detailed |
| format | No | Output format (default: markdown) | markdown |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. It mentions listing 'recent errors' but doesn't specify time ranges, pagination, rate limits, authentication requirements, or what 'frequency patterns' entails. For a read operation with no annotation coverage, this leaves significant gaps in understanding how the tool behaves beyond basic functionality.
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 appropriately sized with two sentences that are front-loaded with the core purpose. The first sentence states the main action, and the second adds useful context about what can be viewed. There's no wasted text, though it could be slightly more structured for clarity.
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 no annotations and no output schema, the description is moderately complete for a read tool with 4 parameters. It covers the basic purpose and some output details but lacks behavioral context like error handling, data freshness, or integration with siblings. For a tool in this context, it meets a minimum viable level but has clear gaps in guidance and transparency.
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%, so the schema fully documents all parameters. The description adds no additional meaning beyond what's in the schema—it doesn't explain parameter interactions, default behaviors, or provide examples. With high schema coverage, the baseline is 3, as the description doesn't compensate but also doesn't detract from the schema's completeness.
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 verb ('List') and resource ('error events from a specific Sentry project'), making the purpose understandable. It distinguishes from some siblings like 'list_projects' or 'list_project_issues' by specifying error events, but doesn't explicitly differentiate from 'list_issue_events' or 'search_errors_in_file', which appear related. The mention of 'recent errors, frequency patterns, and occurrence timestamps' adds specificity but doesn't fully resolve sibling ambiguity.
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 provides no guidance on when to use this tool versus alternatives. It doesn't mention siblings like 'list_issue_events' or 'search_errors_in_file', which likely serve similar purposes, nor does it specify prerequisites such as needing project access. The context is implied through the resource focus but lacks explicit usage rules or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_issue_eventsC
List events for a specific Sentry issue. Analyze event details, metadata, and patterns.
| Name | Required | Description | Default |
|---|---|---|---|
| organization_slug | Yes | The slug of the organization the issue belongs to | |
| issue_id | Yes | The ID of the issue to list events for | |
| view | No | View type (default: detailed) | detailed |
| format | No | Output format (default: markdown) | markdown |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It mentions analyzing 'event details, metadata, and patterns', which hints at output behavior, but lacks critical details like whether this is a read-only operation, if it requires authentication, pagination handling, rate limits, or what 'analyze' entails. The description is too vague for a mutation-sensitive context.
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, efficient sentence that front-loads the core purpose. However, the phrase 'Analyze event details, metadata, and patterns' is somewhat vague and could be more precise. Overall, it's appropriately sized with minimal waste.
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 no annotations and no output schema, the description is incomplete for a tool with 4 parameters. It fails to address key behavioral aspects like safety (read vs. write), authentication needs, or output format details. For a list operation in a potentially complex system like Sentry, more context is needed to ensure proper agent usage.
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%, so the schema fully documents all parameters. The description adds no additional meaning beyond what's in the schema—it doesn't explain parameter interactions, default behaviors, or practical usage examples. Baseline score of 3 is appropriate as the schema does the heavy lifting.
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 verb 'List' and resource 'events for a specific Sentry issue', making the purpose unambiguous. It distinguishes from siblings like 'list_error_events_in_project' by focusing on issue-specific events rather than project-wide errors. However, it doesn't explicitly differentiate from 'get_sentry_event' which might retrieve a single event.
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 provides no guidance on when to use this tool versus alternatives. It doesn't mention when to choose 'list_issue_events' over 'list_error_events_in_project' or 'get_sentry_event', nor does it specify prerequisites like needing an issue ID. Usage is implied but not explicitly stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_organization_replaysC
List replays from a Sentry organization. Monitor user sessions, interactions, errors, and experience issues.
| Name | Required | Description | Default |
|---|---|---|---|
| organization_slug | Yes | The slug of the organization to list replays from | |
| project_ids | No | Optional array of project IDs to filter replays by | |
| environment | No | Optional environment to filter replays by | |
| stats_period | No | Optional time range in format <number><unit> (e.g., '1d' for one day). Units: m (minutes), h (hours), d (days), w (weeks) | |
| start | No | Optional start of time range (UTC ISO8601 or epoch seconds). Use with 'end' instead of 'stats_period' | |
| end | No | Optional end of time range (UTC ISO8601 or epoch seconds). Use with 'start' instead of 'stats_period' | |
| sort | No | Optional field to sort results by | |
| query | No | Optional structured query string to filter results | |
| per_page | No | Optional limit on number of results to return | |
| cursor | No | Optional cursor for pagination | |
| format | No | Output format (default: markdown) | markdown |
| view | No | View type (default: detailed) | detailed |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. While 'List replays' implies a read-only operation, it doesn't explicitly state this or address other behavioral aspects like pagination behavior (though cursor parameter hints at it), rate limits, authentication requirements, data freshness, or what constitutes a 'replay' in Sentry's context. The description adds minimal behavioral context beyond the basic operation.
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 appropriately concise with two sentences that both add value. The first sentence states the core operation clearly, and the second provides helpful domain context about what replays monitor. There's no wasted verbiage or redundancy. While it could be slightly more structured with usage guidance, it's efficiently written.
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?
For a 12-parameter tool with no annotations and no output schema, the description is minimally adequate. It establishes the tool's purpose and domain context but leaves significant gaps: no behavioral transparency, no usage guidance, no explanation of return values or format implications. The high parameter count and lack of output schema suggest more contextual information would be helpful for effective tool selection and use.
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%, providing comprehensive parameter documentation. The description adds no specific parameter semantics beyond what's already in the schema. It doesn't explain relationships between parameters (e.g., stats_period vs start/end), typical values, or how parameters interact with the monitoring context mentioned. The baseline of 3 is appropriate given the schema does all the heavy lifting.
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 tool's purpose: 'List replays from a Sentry organization' with the specific resource (replays) and domain context (Sentry). It distinguishes from some siblings like list_projects or list_issue_events by focusing on replays, though it doesn't explicitly differentiate from all siblings. The additional context about monitoring sessions, interactions, errors, and experience issues provides helpful domain framing.
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 provides no guidance on when to use this tool versus alternatives. While it mentions monitoring user sessions and errors, it doesn't specify scenarios where replays would be preferred over other sibling tools like list_error_events_in_project or get_sentry_event. There's no mention of prerequisites, limitations, or typical use cases for replay data versus other Sentry data types.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_project_issuesC
List issues from a Sentry project. Monitor issue status, severity, frequency, and timing.
| Name | Required | Description | Default |
|---|---|---|---|
| organization_slug | Yes | The slug of the organization the project belongs to | |
| project_slug | Yes | The slug of the project to list issues from | |
| view | No | View type (default: detailed) | detailed |
| format | No | Output format (default: markdown) | markdown |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions monitoring 'issue status, severity, frequency, and timing', which hints at what information is returned, but lacks details on pagination, rate limits, authentication requirements, or error handling. For a list operation with zero annotation coverage, this leaves significant gaps in understanding how the tool behaves.
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 concise with two sentences that efficiently convey the core purpose and monitoring aspects. It's front-loaded with the main action, though the second sentence could be more tightly integrated or omitted if it doesn't add critical value beyond the first.
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 tool's complexity (4 parameters, no output schema, no annotations), the description is insufficient. It doesn't explain return values, error conditions, or how parameters like 'view' and 'format' impact the output. For a list tool with monitoring claims, more context is needed to guide effective use.
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%, so the input schema fully documents all parameters. The description adds no additional parameter semantics beyond what's in the schema, such as explaining how 'view' or 'format' affect the output. This meets the baseline score when the schema does the heavy lifting.
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 ('List issues') and resource ('from a Sentry project'), making the purpose immediately understandable. However, it doesn't explicitly differentiate this tool from sibling tools like 'get_sentry_issue' or 'list_issue_events', which appear to have overlapping functionality with issues.
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 provides no guidance on when to use this tool versus alternatives like 'get_sentry_issue' or 'list_issue_events'. It mentions monitoring aspects but doesn't specify use cases, prerequisites, or exclusions, leaving the agent to infer usage from context alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_projectsC
List accessible Sentry projects. View project slugs, IDs, status, settings, features, and organization details.
| Name | Required | Description | Default |
|---|---|---|---|
| organization_slug | Yes | The slug of the organization to list projects from | |
| view | No | View type (default: detailed) | detailed |
| format | No | Output format (default: markdown) | markdown |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'accessible' projects which implies some permission/visibility constraints, but doesn't specify authentication requirements, rate limits, pagination behavior, or what happens with invalid organization slugs. For a read operation with zero annotation coverage, this leaves significant behavioral gaps.
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, efficient sentence that front-loads the core purpose. It could be slightly more structured by separating scope from output details, but there's no wasted text. Every element serves a purpose, though it could benefit from clearer organization.
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?
For a read/list tool with 3 parameters (100% schema coverage) but no annotations or output schema, the description is minimally adequate. It covers what the tool does and what information it returns, but lacks behavioral context (permissions, errors, pagination) and usage guidance relative to siblings. The absence of output schema means the description should ideally mention return format expectations.
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%, so the schema already fully documents all three parameters. The description doesn't add any parameter-specific information beyond what's in the schema. It mentions viewing 'project slugs, IDs, status, settings, features, and organization details' which aligns with the 'view' parameter options, but doesn't provide additional semantic context. Baseline 3 is appropriate when schema does the heavy lifting.
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 verb ('List') and resource ('accessible Sentry projects'), and specifies the scope ('accessible') and what information is included ('project slugs, IDs, status, settings, features, and organization details'). It distinguishes from siblings like 'create_project' by being a read operation, but doesn't explicitly differentiate from other list tools like 'list_project_issues' or 'list_organization_replays'.
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 provides no guidance on when to use this tool versus alternatives like 'list_project_issues' or 'list_organization_replays'. It mentions 'accessible' projects but doesn't explain what makes a project accessible or any prerequisites. There's no explicit when/when-not usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
resolve_short_idC
Retrieve details about an issue using its short ID. Maps short IDs to issue details, project context, and status.
| Name | Required | Description | Default |
|---|---|---|---|
| organization_slug | Yes | The slug of the organization the issue belongs to | |
| short_id | Yes | The short ID of the issue to resolve (e.g., PROJECT-123) | |
| format | No | Output format (default: markdown) | markdown |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions what gets retrieved ('issue details, project context, and status') but lacks critical information: whether this is a read-only operation, authentication requirements, rate limits, error handling, or response format details. For a tool with no annotations, this leaves significant gaps in understanding its behavior.
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 concise and front-loaded, stating the core purpose in the first sentence. The second sentence adds useful context about what details are retrieved. Both sentences earn their place, with no wasted words, though it could be slightly more structured (e.g., bullet points for retrieved details).
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 no annotations and no output schema, the description is incomplete for a tool with 3 parameters. It covers the basic purpose but misses behavioral traits (e.g., safety, auth), usage context vs. siblings, and output details. For a retrieval tool in a complex environment with many siblings, this leaves the agent under-informed about how to effectively use it.
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%, so the schema already documents all parameters thoroughly. The description adds minimal value beyond the schema: it implies the 'short_id' format (e.g., 'PROJECT-123') but doesn't elaborate on 'organization_slug' or 'format' usage. With high schema coverage, the baseline score of 3 is appropriate, as the description doesn't significantly enhance parameter understanding.
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 tool's purpose: 'Retrieve details about an issue using its short ID.' It specifies the verb ('Retrieve'), resource ('issue details'), and scope ('short ID'). However, it doesn't explicitly differentiate from sibling tools like 'get_sentry_issue' or 'list_project_issues', which might also retrieve issue details through different mechanisms.
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 provides minimal guidance: it implies usage when you have a short ID (e.g., 'PROJECT-123'), but offers no explicit when-to-use vs. alternatives, prerequisites, or exclusions. For instance, it doesn't clarify when to use this tool over 'get_sentry_issue' or other issue-related siblings, leaving the agent to guess based on parameter differences alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_errors_in_fileC
Search for Sentry errors occurring in a specific file. Find all issues related to a particular file path or filename.
| Name | Required | Description | Default |
|---|---|---|---|
| organization_slug | Yes | The slug of the organization in Sentry | |
| project_slug | Yes | The slug of the project in Sentry | |
| file_identifier | Yes | The path or name of the file to search for errors in | |
| identifier_type | Yes | Whether to search by filename or full filepath | |
| format | No | Output format (default: markdown) | markdown |
| view | No | Level of detail in results (default: detailed) | detailed |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It describes a search operation but lacks behavioral details: no mention of permissions needed, rate limits, pagination, error handling, or what 'errors' and 'issues' mean in Sentry context. The description is minimal and doesn't compensate for missing annotations, leaving key operational traits undisclosed.
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 two concise sentences with zero waste, front-loading the core purpose. It could be slightly more structured by separating usage notes, but it efficiently communicates the essential function without redundancy. Every sentence earns its place, though it lacks depth due to brevity.
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 no annotations, no output schema, and a search tool with 6 parameters, the description is incomplete. It doesn't explain return values, error conditions, or behavioral traits like authentication needs. While the schema covers parameters well, the description fails to provide sufficient context for safe and effective use, especially for a tool interacting with an external system like Sentry.
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%, so parameters are well-documented in the schema. The description adds minimal value beyond the schema: it mentions 'file path or filename' and 'search for errors', which aligns with 'file_identifier' and the tool's purpose but doesn't provide additional syntax, examples, or constraints. Baseline 3 is appropriate as the schema does the heavy lifting.
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 tool's purpose: 'Search for Sentry errors occurring in a specific file' with the verb 'search' and resource 'Sentry errors'. It distinguishes from siblings like 'list_project_issues' by specifying file-based filtering, though it doesn't explicitly name alternatives. The description is specific but could be more precise about sibling differentiation.
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 provides no guidance on when to use this tool versus alternatives. It mentions 'Find all issues related to a particular file path or filename' but doesn't specify prerequisites, exclusions, or compare to siblings like 'list_project_issues' or 'get_sentry_issue'. Without usage context, the agent must infer based on tool names alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
setup_sentryC
Set up Sentry for a project returning a dsn and instructions for setup.
| Name | Required | Description | Default |
|---|---|---|---|
| organization_slug | Yes | The slug of the organization to create the project in | |
| team_slug | Yes | The slug of the team to associate the project with | |
| project_name | Yes | The name of the project to create | |
| environment | No | Optional environment name (e.g., production, staging, development) | |
| format | No | Output format (default: markdown) | markdown |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool 'Set up Sentry' and returns outputs, but doesn't clarify if this creates resources, requires specific permissions, has side effects, or handles errors. For a setup tool with zero annotation coverage, this is a significant gap in transparency.
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, efficient sentence that front-loads the purpose and outputs without unnecessary details. Every word earns its place, making it highly concise and well-structured.
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 of a setup tool with no annotations and no output schema, the description is incomplete. It doesn't explain what 'Set up Sentry' entails (e.g., creation, configuration), potential impacts, or return values beyond mentioning 'dsn and instructions'. More context is needed for adequate understanding.
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%, so the schema fully documents all 5 parameters. The description adds no additional meaning beyond what's in the schema, such as explaining relationships between parameters or usage examples. Baseline 3 is appropriate when the schema does the heavy lifting.
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 ('Set up Sentry') and the resource ('for a project'), and specifies the outputs ('returning a dsn and instructions for setup'). However, it doesn't explicitly differentiate from sibling tools like 'create_project', which might have overlapping functionality. The purpose is clear but lacks sibling distinction.
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 provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an organization and team), exclusions, or comparisons to sibling tools like 'create_project' or 'list_projects'. Usage is implied but not explicitly defined.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
11 tool updates
v1.0.0- Added
create_project - Added
get_sentry_event - Added
get_sentry_issue - Added
list_error_events_in_project - Added
list_issue_events - Added
list_organization_replays - Added
list_project_issues - Added
list_projects - Added
resolve_short_id - Added
search_errors_in_file - Added
setup_sentry
TDQS
Most tools have distinct purposes, but there is some overlap between 'list_project_issues' and 'list_error_events_in_project'—both list issues/errors for a project, which could cause confusion. Other tools like 'get_sentry_event' and 'get_sentry_issue' are clearly differentiated by focusing on events vs. issues.
All tool names follow a consistent verb_noun pattern with underscores, such as 'create_project', 'list_projects', and 'get_sentry_event'. There are no deviations in naming conventions, making the set predictable and easy to understand.
With 11 tools, the count is well-scoped for a Sentry integration, covering key operations like project management, issue/event retrieval, listing, and setup. Each tool appears to serve a specific purpose without being excessive or insufficient.
The toolset provides good coverage for monitoring and debugging in Sentry, including CRUD-like operations (create, list, get) for projects, issues, and events. A minor gap is the lack of update or delete tools for issues or projects, which agents might need for full lifecycle management, but core workflows are well-supported.
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