What can you do with this server?

The Prometheus MCP Server provides a Model Context Protocol (MCP) interface for AI assistants to interact with Prometheus metrics data. You can: * Execute PromQL Queries: Run both instant queries and range queries (with specified time ranges and step intervals) * Discover Metrics: List all available metrics and retrieve metadata for specific metrics * Get Scrape Targets: Retrieve information about all configured scrape targets * Authentication Support: Connect using Basic or Bearer token authentication * Docker Deployment: Easily deploy and run using Docker or Docker Compose * Configurable Tools: Customize available tools to optimize context window usage

Which integrations are available for this server?

Provides access to Prometheus metrics and queries, allowing execution of PromQL queries, metrics discovery and exploration, viewing instant and range query results, and retrieving target information from a Prometheus server.

How do I use Prometheus MCP Server?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@Prometheus MCP Server show me the top 5 CPU usage metrics over the last hour" 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.

de en es ja ko ru zh

Prometheus MCP Server

by pab1it0

Overview Schema Related Servers Score Discussions

Python

Remote

Prometheus MCP Server

GitHub Container Registry Helm Chart GitHub Release Codecov Python License

Give AI assistants the power to query your Prometheus metrics.

A Model Context Protocol (MCP) server that provides access to your Prometheus metrics and queries through standardized MCP interfaces, allowing AI assistants to execute PromQL queries and analyze your metrics data.

Getting Started

Prerequisites

Prometheus server accessible from your environment
MCP-compatible client (Claude Desktop, VS Code, Cursor, Windsurf, etc.)

Installation Methods

Add to your Claude Desktop configuration:

{
  "mcpServers": {
    "prometheus": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "PROMETHEUS_URL",
        "ghcr.io/pab1it0/prometheus-mcp-server:latest"
      ],
      "env": {
        "PROMETHEUS_URL": "<your-prometheus-url>"
      }
    }
  }
}

Install via the Claude Code CLI:

claude mcp add prometheus --env PROMETHEUS_URL=http://your-prometheus:9090 -- docker run -i --rm -e PROMETHEUS_URL ghcr.io/pab1it0/prometheus-mcp-server:latest

Add to your MCP settings in the respective IDE:

{
  "prometheus": {
    "command": "docker",
    "args": [
      "run",
      "-i",
      "--rm",
      "-e",
      "PROMETHEUS_URL",
      "ghcr.io/pab1it0/prometheus-mcp-server:latest"
    ],
    "env": {
      "PROMETHEUS_URL": "<your-prometheus-url>"
    }
  }
}

The easiest way to run the Prometheus MCP server is through Docker Desktop:

Via MCP Catalog: Visit the Prometheus MCP Server on Docker Hub and click the button above
Via MCP Toolkit: Use Docker Desktop's MCP Toolkit extension to discover and install the server
Configure your connection using environment variables (see Configuration Options below)

Run directly with Docker:

# With environment variables
docker run -i --rm \
  -e PROMETHEUS_URL="http://your-prometheus:9090" \
  ghcr.io/pab1it0/prometheus-mcp-server:latest

# With authentication
docker run -i --rm \
  -e PROMETHEUS_URL="http://your-prometheus:9090" \
  -e PROMETHEUS_USERNAME="admin" \
  -e PROMETHEUS_PASSWORD="password" \
  ghcr.io/pab1it0/prometheus-mcp-server:latest

Deploy to Kubernetes using the Helm chart from the OCI registry:

helm install prometheus-mcp-server \
  oci://ghcr.io/pab1it0/charts/prometheus-mcp-server \
  --version 1.1.1 \
  --set prometheus.url="http://prometheus:9090"

With authentication:

helm install prometheus-mcp-server \
  oci://ghcr.io/pab1it0/charts/prometheus-mcp-server \
  --version 1.1.1 \
  --set prometheus.url="http://prometheus:9090" \
  --set auth.username="admin" \
  --set auth.password="secret"

With a custom values file:

helm install prometheus-mcp-server \
  oci://ghcr.io/pab1it0/charts/prometheus-mcp-server \
  --version 1.1.1 \
  -f values.yaml

See the chart values for all available configuration options.

Configuration Options

Variable	Description	Required
`PROMETHEUS_URL`	URL of your Prometheus server	Yes
`PROMETHEUS_URL_SSL_VERIFY`	Set to False to disable SSL verification	No
`PROMETHEUS_DISABLE_LINKS`	Set to True to disable Prometheus UI links in query results (saves context tokens)	No
`PROMETHEUS_REQUEST_TIMEOUT`	Request timeout in seconds to prevent hanging requests (DDoS protection)	No (default: 30)
`PROMETHEUS_USERNAME`	Username for basic authentication	No
`PROMETHEUS_PASSWORD`	Password for basic authentication	No
`PROMETHEUS_TOKEN`	Bearer token for authentication	No
`PROMETHEUS_CLIENT_CERT`	Path to client certificate file for mutual TLS authentication	No
`PROMETHEUS_CLIENT_KEY`	Path to client private key file for mutual TLS authentication	No
`REQUESTS_CA_BUNDLE`	Path to CA bundle file for verifying the server's TLS certificate (standard `requests` library env var)	No
`ORG_ID`	Organization ID for multi-tenant setups	No
`PROMETHEUS_MCP_SERVER_TRANSPORT`	Transport mode (stdio, http, sse)	No (default: stdio)
`PROMETHEUS_MCP_BIND_HOST`	Host for HTTP transport	No (default: 127.0.0.1)
`PROMETHEUS_MCP_BIND_PORT`	Port for HTTP transport	No (default: 8080)
`PROMETHEUS_MCP_STATELESS_HTTP`	Enable stateless HTTP mode for multi-replica support	No (default: False)
`PROMETHEUS_CUSTOM_HEADERS`	Custom headers as JSON string	No
`TOOL_PREFIX`	Prefix for all tool names (e.g., `staging` results in `staging_execute_query`). Useful for running multiple instances targeting different environments in Cursor	No

Related MCP server: Prometheus MCP Server

Available Tools

Tool	Category	Description
`health_check`	System	Health check endpoint for container monitoring and status verification
`execute_query`	Query	Execute a PromQL instant query against Prometheus
`execute_range_query`	Query	Execute a PromQL range query with start time, end time, and step interval
`list_metrics`	Discovery	List all available metrics in Prometheus with pagination and filtering support
`get_metric_metadata`	Discovery	Get metadata for one metric or bulk metadata with optional filtering
`get_targets`	Discovery	Get scrape targets, with server-side `state`/`scrape_pool` filtering and optional pagination

The list of tools is configurable, so you can choose which tools you want to make available to the MCP client. This is useful if you don't use certain functionality or if you don't want to take up too much of the context window.

Features

Execute PromQL queries against Prometheus
Discover and explore metrics
- List available metrics
- Get metadata for specific metrics
- Search metric metadata by name or description in a single call
- View instant query results
- View range query results with different step intervals
Authentication support
- Basic auth from environment variables
- Bearer token auth from environment variables
Docker containerization support
Provide interactive tools for AI assistants

Development

Contributions are welcome! Please see our Contributing Guide for detailed information on how to get started, coding standards, and the pull request process.

This project uses uv to manage dependencies. Install uv following the instructions for your platform:

curl -LsSf https://astral.sh/uv/install.sh | sh

You can then create a virtual environment and install the dependencies with:

uv venv
source .venv/bin/activate  # On Unix/macOS
.venv\Scripts\activate     # On Windows
uv pip install -e .

Testing

The project includes a comprehensive test suite that ensures functionality and helps prevent regressions.

Run the tests with pytest:

# Install development dependencies
uv pip install -e ".[dev]"

# Run the tests
pytest

# Run with coverage report
pytest --cov=src --cov-report=term-missing

When adding new features, please also add corresponding tests.

License

MIT

Available Tools

6 tools

execute_queryExecute PromQL QueryC

Read-onlyIdempotent

Execute a PromQL instant query against Prometheus

ParametersJSON Schema

Name	Required	Description	Default
`query`	Yes
`time`	No

Output Schema

ParametersJSON Schema

Name	Required	Description
No output parameters

TDQS

C2.7/5.0

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already provide readOnlyHint, destructiveHint, idempotentHint, and openWorldHint. The description adds no behavioral context beyond what is in the schema and annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence, which is concise but overly terse. It could be improved with more structure while remaining short.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With 0% schema coverage and no description of parameters, the tool is incomplete for an agent. The output schema exists, but the description does not mention it or the nature of the return value.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, yet the description does not explain the parameters. It fails to clarify that 'query' is the PromQL expression and 'time' is optional evaluation time.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Execute') and the resource ('PromQL instant query against Prometheus'). It distinguishes from the sibling tool 'execute_range_query' which handles range queries.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives like 'execute_range_query'. There is no mention of typical use cases or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

execute_range_queryExecute PromQL Range QueryB

Read-onlyIdempotent

Execute a PromQL range query with start time, end time, and step interval

ParametersJSON Schema

Name	Required	Description	Default
`query`	Yes
`start`	Yes
`end`	Yes
`step`	Yes

Output Schema

ParametersJSON Schema

Name	Required	Description
No output parameters

TDQS

B3.4/5.0

Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate read-only, idempotent, and non-destructive behavior. The description adds that it uses PromQL with time parameters, but does not disclose potential failures, pagination, or rate limits. For a tool with rich annotations, the description adds modest extra context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded sentence with no extraneous words. It efficiently communicates the core action and key parameters.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 4-parameter tool with an output schema and comprehensive annotations, the description provides adequate context. It names the parameters and states the tool's purpose. Minor gaps include lack of format details and error behavior, but overall it is mostly complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description partially compensates by naming the parameters (start time, end time, step interval). However, it does not specify expected formats (e.g., Unix timestamps or RFC3339) or explain the query parameter beyond 'PromQL range query', leaving ambiguity.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool executes a PromQL range query with start time, end time, and step interval. However, it does not distinguish this from the sibling tool 'execute_query', which likely handles instant queries, missing an opportunity for differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No usage guidance is provided. The description does not specify when to use this tool over alternatives (e.g., for time-range versus instant queries), nor does it mention prerequisites or conditions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

get_metric_metadataGet Metric MetadataA

Read-onlyIdempotent

Get metadata (type, help, unit) for metrics. Returns all metric metadata when no metric name is provided. Use filter_pattern to search metric names and descriptions.

ParametersJSON Schema

Name	Required	Description	Default
`metric`	No
`filter_pattern`	No
`limit`	No
`offset`	No

Output Schema

ParametersJSON Schema

Name	Required	Description
`result`	Yes

TDQS

A4.2/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint, destructiveHint, idempotentHint, openWorldHint. The description adds that it returns all metadata when no metric is given and how to use filter_pattern. No contradictions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two efficient sentences with no redundancy. The first defines purpose, the second provides usage guidance. Every sentence adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With output schema present, description covers primary functionality. However, it omits explanation of pagination parameters (limit, offset), which could be important for large result sets. Otherwise complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so description must compensate. It explains metric (optional, returns all if null) and filter_pattern (search). But it does not cover limit/offset, leaving pagination behavior unclear. Adequate but not fully compensating.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool retrieves metadata (type, help, unit) for metrics. It specifies behavior when no metric name is provided (returns all) and mentions filter_pattern for searching. This distinguishes it from siblings like list_metrics and execute_query.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit guidance on using filter_pattern to search. However, it does not mention when not to use the tool or alternatives, but the context is clear enough for an agent to decide.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

get_targetsGet Scrape TargetsA

Read-onlyIdempotent

Get information about all scrape targets

ParametersJSON Schema

Name	Required	Description	Default
No parameters

Output Schema

ParametersJSON Schema

Name	Required	Description
No output parameters

TDQS

A4/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate readOnlyHint=true and destructiveHint=false, so the description reinforces that it is a read operation. It adds that it returns information about all scrape targets, but does not detail what information is included. The output schema likely covers the return format.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence of 8 words, front-loaded with the key action and resource. Every word is meaningful with no redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with no parameters and an existing output schema, the description is reasonably complete. It states the purpose and scope (all targets). A minor gap is the lack of mention of potential pagination or limits, but the output schema likely handles that.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, and schema description coverage is trivially 100%. The description does not need to add parameter details. The baseline for 0 parameters is 4, and no additional information is necessary.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'Get' and the resource 'scrape targets', indicating it retrieves information on all scrape targets. It distinguishes from sibling tools like execute_query or get_metric_metadata which perform different operations.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

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, such as when to use list_metrics or get_metric_metadata. It lacks explicit context or exclusions for sibling tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

health_checkHealth CheckA

Read-onlyIdempotent

Health check endpoint for container monitoring and status verification

ParametersJSON Schema

Name	Required	Description	Default
No parameters

Output Schema

ParametersJSON Schema

Name	Required	Description
No output parameters

TDQS

A4.3/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint, destructiveHint, idempotentHint, and openWorldHint. The description adds context about container monitoring and status verification, which aligns with annotations and provides additional behavioral clarity.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Single sentence, front-loaded with key information, no wasted words. Highly concise and well-structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given zero parameters and an existing output schema (indicated by 'has output schema: true'), the description is complete enough to understand the tool's purpose and basic behavior.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

No parameters are defined, and schema coverage is 100%. Baseline score of 4 applies since the description does not need to compensate for missing parameter details.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it is a health check endpoint for container monitoring and status verification. Specific verb and resource, and it clearly distinguishes from sibling tools like execute_query and list_metrics.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for checking system status but does not provide explicit guidance on when to use versus alternatives or when not to use. Usage is implied by the tool's purpose and sibling context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

list_metricsList Available MetricsA

Read-onlyIdempotent

List all available metrics in Prometheus with optional pagination support

ParametersJSON Schema

Name	Required	Description	Default
`limit`	No
`offset`	No
`filter_pattern`	No
`refresh_cache`	No

Output Schema

ParametersJSON Schema

Name	Required	Description
No output parameters

TDQS

A3.7/5.0

Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true, so the description's note about pagination adds minor behavioral context but is not necessary for safety awareness. No contradictions with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence of 10 words, directly stating the purpose and key feature. No unnecessary information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description does not cover the purpose of filter_pattern or refresh_cache, nor how pagination behaves (defaults, total count). Given 4 undocumented parameters, the description is incomplete for a full understanding.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%. The description only hints at pagination (limit/offset) but does not explain filter_pattern or refresh_cache. It fails to compensate for missing schema descriptions on 4 parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'List all available metrics in Prometheus', specifying the exact resource and action. It distinguishes itself from sibling tools like execute_query and get_metric_metadata by focusing on enumeration of metrics.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description mentions optional pagination, indicating when to use pagination parameters. However, it lacks explicit guidance on when to use this tool versus alternatives like get_metric_metadata for detailed metric information.

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.

6 tool updatesv1.2.2May 1, 2026
- Changedexecute_query3 fields changed
  - addedInput schema / additionalProperties
```
Added value: +false
```
  - removedInput schema / properties / query / title
```
Removed value: -"Query"
```
  - removedInput schema / properties / time / title
```
Removed value: -"Time"
```
- Changedexecute_range_query5 fields changed
  - addedInput schema / additionalProperties
```
Added value: +false
```
  - removedInput schema / properties / end / title
```
Removed value: -"End"
```
  - removedInput schema / properties / query / title
```
Removed value: -"Query"
```
  - removedInput schema / properties / start / title
```
Removed value: -"Start"
```
  - removedInput schema / properties / step / title
```
Removed value: -"Step"
```
- Changedget_metric_metadata14 fields changed
  - addedInput schema / additionalProperties
```
Added value: +false
```
  - addedInput schema / properties / filter_pattern
```
Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null
+}
```
  - addedInput schema / properties / limit
```
Added value: +{
+  "anyOf": [
+    {
+      "type": "integer"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null
+}
```
  - addedInput schema / properties / metric / anyOf
```
Added value: +[
+  {
+    "type": "string"
+  },
+  {
+    "type": "null"
+  }
+]
```
  - addedInput schema / properties / metric / default
```
Added value: +null
```
  - removedInput schema / properties / metric / title
```
Removed value: -"Metric"
```
  - removedInput schema / properties / metric / type
```
Removed value: -"string"
```
  - addedInput schema / properties / offset
```
Added value: +{
+  "default": 0,
+  "type": "integer"
+}
```
  - removedInput schema / required
```
Removed value: -[
-  "metric"
-]
```
  - addedOutput schema / properties / result / anyOf
```
Added value: +[
+  {
+    "items": {
+      "additionalProperties": true,
+      "type": "object"
+    },
+    "type": "array"
+  },
+  {
+    "additionalProperties": true,
+    "type": "object"
+  }
+]
```
  - removedOutput schema / properties / result / items
```
Removed value: -{
-  "additionalProperties": true,
-  "type": "object"
-}
```
  - removedOutput schema / properties / result / title
```
Removed value: -"Result"
```
  - removedOutput schema / properties / result / type
```
Removed value: -"array"
```
  - removedOutput schema / title
```
Removed value: -"_WrappedResult"
```
- Changedget_targets1 field changed
  - addedInput schema / additionalProperties
```
Added value: +false
```
- Changedhealth_check1 field changed
  - addedInput schema / additionalProperties
```
Added value: +false
```
- Changedlist_metrics5 fields changed
  - addedInput schema / additionalProperties
```
Added value: +false
```
  - removedInput schema / properties / filter_pattern / title
```
Removed value: -"Filter Pattern"
```
  - removedInput schema / properties / limit / title
```
Removed value: -"Limit"
```
  - removedInput schema / properties / offset / title
```
Removed value: -"Offset"
```
  - addedInput schema / properties / refresh_cache
```
Added value: +{
+  "default": false,
+  "type": "boolean"
+}
```

6 tool updatesv1.0.0Jan 3, 2026

Changedexecute_query2 fields changed

removedInput schema / title

Removed value: -"execute_queryArguments"

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "additionalProperties": true,
+  "type": "object"
+}

Changedexecute_range_query2 fields changed

removedInput schema / title

Removed value: -"execute_range_queryArguments"

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "additionalProperties": true,
+  "type": "object"
+}

Changedget_metric_metadata2 fields changed

removedInput schema / title

Removed value: -"get_metric_metadataArguments"

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "properties": {
+    "result": {
+      "items": {
+        "additionalProperties": true,
+        "type": "object"
+      },
+      "title": "Result",
+      "type": "array"
+    }
+  },
+  "required": [
+    "result"
+  ],
+  "title": "_WrappedResult",
+  "type": "object",
+  "x-fastmcp-wrap-result": true
+}

Changedget_targets2 fields changed

removedInput schema / title
```
Removed value: -"get_targetsArguments"
```

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "additionalProperties": {
+    "items": {
+      "additionalProperties": true,
+      "type": "object"
+    },
+    "type": "array"
+  },
+  "type": "object"
+}

Addedhealth_check

Changedlist_metrics5 fields changed

addedInput schema / properties / filter_pattern

Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "title": "Filter Pattern"
+}

addedInput schema / properties / limit

Added value: +{
+  "anyOf": [
+    {
+      "type": "integer"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "title": "Limit"
+}

addedInput schema / properties / offset

Added value: +{
+  "default": 0,
+  "title": "Offset",
+  "type": "integer"
+}

removedInput schema / title
```
Removed value: -"list_metricsArguments"
```

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "additionalProperties": true,
+  "type": "object"
+}

5 tool updatesMay 3, 2025
- First observedexecute_query
- First observedexecute_range_query
- First observedget_metric_metadata
- First observedget_targets
- First observedlist_metrics

Install Server

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TDQS

A3.7/5.0

Disambiguation5/5

Each tool has a clearly distinct purpose: query types (instant vs range), metadata retrieval, target info, health check, and metric listing. No overlap.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern in snake_case (e.g., execute_query, get_metric_metadata). No deviations.

Tool Count5/5

Six tools cover the essential Prometheus operations without being excessive or insufficient. Well-scoped for the server's purpose.

Completeness4/5

Core CRUD-like operations for queries and metadata are present. Minor gaps like alert management or rule configuration are missing but not critical for the primary use case.

Maintenance

ActivityMaintained

ResponsivenessSyncing

Resources

GitHub Repository

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Reddit Discussion

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