Query Prometheus Metrics with LLMs
A Golang MCP server exposing Prometheus's HTTP API - PromQL queries, targets, rules, TSDB stats, and docs - to LLMs with a token-aware output mode.
Why it matters
Enable LLMs to interact with Prometheus instances, allowing for the generation and execution of PromQL queries, analysis of metrics, and management of monitoring configurations.
Outcomes
What it gets done
Execute PromQL queries and analyze metric data.
Access Prometheus configurations and build information.
Search and read official Prometheus documentation.
Discover Prometheus targets and alert managers.
Install
Add it to your toolbox
Run in your project directory:
curl -fsSL https://spark.entire.vc/get/vb-prometheus-golang | bash Capabilities
Tools your agent gets
Get an overview of Prometheus Alertmanager discovery
Get Prometheus build information
Get Prometheus configuration
List official Prometheus documentation files
Read a named markdown file containing official Prometheus documentation
Search markdown files containing official Prometheus documentation
Execute an exemplars query for a given query and time range
Get runtime flags
Overview
Prometheus (Golang) MCP Server
Exposes Prometheus's HTTP API to LLMs as MCP tools - PromQL queries, target/rule/alert inspection, docs search, and TSDB internals - with optional TOON output and response truncation for token efficiency. Use for LLM-driven Prometheus investigation, diagnostics, and reporting; TSDB Admin tools that can delete data are disabled by default and require an explicit opt-in flag.
What it does
Prometheus MCP Server lets LLMs interact with a running Prometheus instance through its HTTP API, generating and executing PromQL queries, listing and analyzing metrics, checking targets and alerting/recording rules, and reading official Prometheus documentation. Tools span several categories: query execution (instant and range queries, exemplar queries, series/label discovery), operational insight (alertmanagers, targets, active alerts, loaded rules, build/runtime info, config, flags), management endpoints (healthy, ready, reload, quit), TSDB internals (tsdb_stats, wal_replay_status), and documentation (docs_list, docs_read, docs_search against the official prometheus/docs repository). A separate, disabled-by-default group of TSDB Admin tools - clean_tombstones, delete_series, and snapshot - can perform destructive operations like deleting data, and only becomes available when the server is explicitly started with a flag acknowledging that risk.
Because the Prometheus API returns JSON, tools return that same JSON structure to the LLM for processing. For token/context-constrained use, the server can optionally convert responses to Token-Oriented Object Notation (TOON), a format designed for token efficiency on uniform arrays of objects (though not guaranteed to reduce usage on complex, non-uniform data), and can truncate API responses to a maximum number of lines or entries, with LLMs able to override the global truncation limit per tool call on supported tools. To keep the tool list manageable for LLMs with smaller context windows, a whitelist of specific tools can be registered instead of the full set; a fixed set of core tools (docs_list, docs_read, docs_search, query, range_query, metric_metadata, label_names, label_values, series) is always loaded regardless.
When to use - and when NOT to
Use this when an LLM needs to investigate slow queries, analyze metric cardinality, review a Prometheus instance's configuration and health, or summarize documentation and best practices - the source's own demos cover exactly these scenarios, including asking Claude to diagnose slow-query root causes and generating SLO recording rules from the server's own metrics. It also works against Prometheus-API-compatible backends like Thanos, though feature parity varies: Thanos, for instance, doesn't implement a centralized config endpoint or several TSDB admin/management endpoints, so the corresponding tools are removed for that backend while an extra list_stores tool is added.
Capabilities
The server exposes its own operational metrics (build info, tool/API call failure counts and durations, docs auto-update status, standard Go/process metrics) on a configurable telemetry path, with a pre-built Grafana dashboard included for visualizing them. Security options include supplying a Prometheus HTTP config file to connect to secured Prometheus instances, and a web configuration file to put basic auth or custom TLS in front of the MCP server's own endpoints.
How to install
Deployment options include a downloadable binary, a Docker image supporting either stdio or streamable HTTP/SSE transport, a Helm chart published as an OCI artifact for Kubernetes, raw Kubernetes/OpenShift manifests, and system packages with an included systemd unit:
docker run --rm -i ghcr.io/tjhop/prometheus-mcp-server:latest --prometheus.url "https://$yourPrometheus:9090"
Configuration is available via command-line flags or matching environment variables, covering the Prometheus URL and timeout, backend selection, transport type, truncation limits, TOON output, and TLS/auth settings.
Who it's for
SRE and observability engineers who want an LLM to query, diagnose, and report on a Prometheus (or Prometheus-compatible) instance directly, with token-efficiency controls for use with smaller-context models.
Source README
Prometheus MCP Server
About
This is an MCP server to allow LLMs to interact with a running Prometheus instance via the API to do things like generate and execute promql queries, list and analyze metrics, etc.
Demos and Examples
Asking Claude to Investigate Slow Queries
The prompt used was:
querying my metrics is slow, can you help me figure out why?
Investigate metrics produced by the MCP server itself and suggest recording rules for SLOs
The prompt used was:
use the tools from the prometheus mcp server to investigate the metrics from
the mcp server and suggest prometheus recording rules for SLOs
Summarize Prometheus metric/label naming best practices
The prompt used was:
summarize prometheus metric/label name best practices
Report on the health of the Prometheus instance that powers prometheus.demo.prometheus.io
The prompt used was:
please provide a comprehensive review and summary of the prometheus server.
review it's configuration, flags, runtime/build info, and anything else that
you feel may provide insight into the status of the prometheus instance,
including analyzing metrics and executing queries
Tools
The Prometheus HTTP API outputs JSON data, and the tools in this MCP server return that JSON to the LLM for processing as it's structured and well understood by LLMs.
LLMs and Token/Context Efficiency
This MCP server supports the following options which have the potential to reduce token/context usage:
TOON Encoding
If token/context usage is a concern, this MCP server also supports converting the API's JSON data to the Token-Oriented Object Notation (TOON) format.
While it is not guaranteed to reduce token usage, it is designed with token efficiency in mind.
As noted on TOON's documentation, it excels at uniform arrays of objects; non-uniform/complex objects may still be more token-efficient in JSON.
Real world token usage will depend on usage patterns, please review common workflows to determine if TOON output may be beneficial.
Please see Flags for more information on the available flags and their corresponding environment variables.
API Response Truncation
This feature allows you to set a maximum limit on the number of lines or entries returned from the Prometheus API for, which can help in reducing the amount of data sent to the LLM.
Setting the limit to 0 disables truncation.
Truncation is disabled by default.
Note that LLMs capable of handling tool request arguments can override this global truncation limit on a per-tool-call basis for supported tools.
Please see Flags for more information on the available flags and their corresponding environment variables.
Full Tool List
| Tool Name | Description |
|---|---|
alertmanagers |
Get overview of Prometheus Alertmanager discovery |
build_info |
Get Prometheus build information |
config |
Get Prometheus configuration |
docs_list |
List of Official Prometheus Documentation Files |
docs_read |
Read the named markdown file containing official Prometheus documentation from the prometheus/docs repo |
docs_search |
Search the markdown files containing official Prometheus documentation from the prometheus/docs repo |
exemplar_query |
Performs a query for exemplars by the given query and time range |
flags |
Get runtime flags |
healthy |
Management API endpoint that can be used to check Prometheus health |
label_names |
Returns the unique label names present in the block in sorted order by given time range and matchers |
label_values |
Performs a query for the values of the given label, time range and matchers |
list_alerts |
List all active alerts |
list_rules |
List all alerting and recording rules that are loaded |
list_targets |
Get overview of Prometheus target discovery |
metric_metadata |
Returns metadata about metrics currently scraped by the metric name |
query |
Execute an instant query against the Prometheus datasource, returning one value per series at a single point in time |
quit |
Management API endpoint that can be used to trigger a graceful shutdown of Prometheus |
range_query |
Execute a range query against the Prometheus datasource, returning values over a time window |
ready |
Management API endpoint that can be used to check Prometheus is ready to serve traffic (i.e. respond to queries |
reload |
Management API endpoint that can be used to trigger a reload of the Prometheus configuration and rule files |
runbooks_list |
List the runbooks embedded in this server: guided workflows (Agent Skills) for common Prometheus tasks |
runbooks_read |
Read the named runbook by skill name (e.g. check-system-health) |
runtime_info |
Get Prometheus runtime information |
series |
Finds series by label matchers |
targets_metadata |
Returns metadata about metrics currently scraped by the target |
tsdb_stats |
Get usage and cardinality statistics from the TSDB |
wal_replay_status |
Get current WAL replay status |
NOTE:
Because the TSDB Admin API endpoints
allow for potentially destructive operations like deleting data, they are not
enabled by default. In order to enable the TSDB Admin API endpoints, the MCP
server must be started with the flag--dangerous.enable-tsdb-admin-toolsto
acknowledge the associated risk these endpoints carry.
| Tool Name | Description |
|---|---|
clean_tombstones |
Removes the deleted data from disk and cleans up the existing tombstones |
delete_series |
deletes data for a selection of series in a time range |
snapshot |
creates a snapshot of all current data into snapshots/ |
Tool Sets
The server exposes many tools to interact with Prometheus. There are tools to interact with Prometheus via the API, as well as additional tools to do things like read documentation, etc.
By default, they are all registered and available for use (TSDB Admin API tools need an extra flag).
To be considerate to LLMs with smaller context windows, it's possible to pass in a whitelist of specific tools to register with the server.
The following 'core' tools are always loaded: [docs_list, docs_read, docs_search, runbooks_list, runbooks_read, query, range_query, metric_metadata, label_names, label_values, series].
Additional tools can be specified with the --mcp.tools flag.
For example, the command line:
prometheus-mcp-server --mcp.tools=build_info --mcp.tools=flags --mcp.tools=runtime_info
Would result in the following tools being loaded:
build_infodocs_listdocs_readdocs_searchflagslabel_nameslabel_valuesmetric_metadataqueryrange_queryrunbooks_listrunbooks_readruntime_infoseries
Runbooks (Agent Skills) and Prompts
The server embeds a set of runbooks: guided workflows for common Prometheus tasks, expressed in terms of the server's tools. Each runbook orients the model on the relevant tools, then suggests topics to explore with example queries rather than prescribing a fixed sequence of steps.
Runbooks cover tasks like system health checks, missing-data triage, error-rate investigation, high-cardinality optimization, recording/alerting rule review, and configuration/performance tuning.
Each runbook is packaged as a full Agent Skill: a directory containing a SKILL.md with name/description frontmatter.
Runbooks are exposed three ways:
- Tools: the model can discover and read them itself via the
runbooks_list/runbooks_readtools when a request matches a runbook's purpose. Tools are the most portable path and work in every MCP client. - Skill resources: per the SEP-2640 skills extension draft, each runbook is a
skill://<name>/SKILL.mdresource, enumerated by the well-knownskill://index.jsondiscovery index, and the server declares theio.modelcontextprotocol/skillsextension capability. Skill-aware hosts can consume these like local filesystem skills; other clients can still read them as ordinary MCP resources. - MCP prompts: each runbook is also registered as an MCP prompt under its skill name (e.g.
check-system-health,optimize-high-cardinality), so clients with prompt support can invoke a guided workflow directly (often surfaced as slash commands).
Prometheus Compatible Backends
There are many Prometheus compatible backends that can be used to extend prometheus in a variety of ways, often with the goals of offering long term storage or query aggregation from multiple prometheus instances.
Some examples can be found in the Remote Storage of prometheus' docs.
Many of those services also offer a "prometheus compatible" API that can be used to query/interact with the data using native promQL.
In general, this MCP server should at a minimum work for other prometheus API compatible services to execute queries and interact with the series/labels/metadata endpoints for metric and label discovery.
Beyond that, there may be API differences as the different systems implement different parts/extensions of the API for their needs.
Examples:
- Thanos does not use a centralized config, so the config endpoint is not implemented and thus the config tool fails.
- Mimir and Cortex implement extra endpoints to manage/add/remove rules
To workaround this and provide a better experience on some of the commonly used Prometheus compatible systems, this project may add direct support for select systems to provide different/more tools.
Choosing a specific prometheus backend implementation can be done with the --prometheus.backend flag.
The list of available backend implementations on a given release of the MCP server can be found in the output of the --help flag.
Qualifications and support criteria are still under consideration, please open an issue to request support/features for a specific backend for further discussion.
Prometheus Backend Implementation Differences
| Backend | Tool | Add/Remove/Change | Notes |
|---|---|---|---|
prometheus |
n/a | none | Standard prometheus tools. Functionally equivalent to --mcp.tools="all". The default MCP server toolset. |
thanos |
alertmanagers |
remove | Thanos does not implement the endpoint and the tool returns a 404. |
thanos |
clean_tombstones |
remove | Prometheus TSDB admin endpoint |
thanos |
config |
remove | Thanos does not use a centralized config, so it doesn't implement the endpoint and the tool returns a 404. |
thanos |
delete_series |
remove | Prometheus TSDB admin endpoint |
thanos |
list_stores |
add | Thanos provides an additional endpoint to list store API servers. |
thanos |
quit |
remove | Thanos does not implement the endpoint and the tool returns a 404. |
thanos |
reload |
remove | Thanos does not implement the endpoint and the tool returns a 404. |
thanos |
snapshot |
remove | Prometheus TSDB admin endpoint |
thanos |
wal_replay_status |
remove | Thanos does not implement the endpoint and the tool returns a 404. |
Resources
| Resource Name | Resource URI | Description |
|---|---|---|
| List of Official Prometheus Documentation Files | prometheus://docs |
List of official Prometheus Documentation files |
| Read Official Prometheus Documentation | prometheus://docs/{+file} |
Read official Prometheus Documentation files by name |
| Agent Skills Discovery Index | skill://index.json |
SEP-2640 discovery index of the embedded runbooks/skills |
| Prometheus Runbook (Agent Skill) | skill://<name>/SKILL.md |
Read the named runbook, packaged as an Agent Skill (one resource per runbook) |
Installation and Usage
This MCP server is most useful when fully integrated with tooling and/or installed as a tool server with another system.
Installation procedures and integration support will vary depending on the tools being used.
For example:
- some systems can only interact with MCP tools and not resources/prompts
- some systems use mcp.json config file format to manage MCP servers and some require custom formats
- some systems don't speak MCP directly and require tools like mcp-to-openapi to proxy
Please check the documentation for the tool being used/integrated for specific instructions and level of support.
Binary
Download a release appropriate for your system from the Releases page.
Please see Flags for more information on the available flags and their corresponding environment variables.
/path/to/prometheus-mcp-server <flags>
# or using env vars
PROMETHEUS_MCP_SERVER_PROMETHEUS_URL="https://$yourPrometheus:9090" /path/to/prometheus-mcp-server
Docker
Please see Flags for more information on the available flags and their corresponding environment variables.
# Stdio transport
docker run --rm -i ghcr.io/tjhop/prometheus-mcp-server:latest --prometheus.url "https://$yourPrometheus:9090"
# or using env vars
docker run --rm -i -e PROMETHEUS_MCP_SERVER_PROMETHEUS_URL="https://$yourPrometheus:9090" ghcr.io/tjhop/prometheus-mcp-server:latest
# Streamable HTTP transport (capable of SSE as well)
docker run --rm -p 8080:8080 ghcr.io/tjhop/prometheus-mcp-server:latest --prometheus.url "https://$yourPrometheus:9090" --mcp.transport "http" --web.listen-address ":8080"
# or using env vars
docker run --rm -p 8080:8080 -e PROMETHEUS_MCP_SERVER_PROMETHEUS_URL="https://$yourPrometheus:9090" -e PROMETHEUS_MCP_SERVER_MCP_TRANSPORT="http" -e PROMETHEUS_MCP_SERVER_WEB_LISTEN_ADDRESS=":8080" ghcr.io/tjhop/prometheus-mcp-server:latest
Helm Chart (Kubernetes)
A Helm chart is available for deploying to Kubernetes. The chart is published as an OCI artifact on each release.
helm install prometheus-mcp-server oci://ghcr.io/tjhop/charts/prometheus-mcp-server \
--version <version> \
--set prometheus.url=http://prometheus:9090
See the chart README for the full list of configuration values and examples.
Kubernetes (Raw Manifests)
If you prefer deploying without Helm, example Kubernetes manifests are available:
System Packages
Download a release appropriate for your system from the Releases page. A Systemd service file is included in the system packages that are built.
# install system package (example assuming Debian based)
apt install /path/to/package
# create unit override, add any needed flags or environment variables
systemctl edit prometheus-mcp-server.service
systemctl enable --now prometheus-mcp-server.service
Note: While packages are built for several systems, there are currently no plans to attempt to submit packages to upstream package repositories.
Security and Authentication
Connecting to Secure Prometheus Instances
The MCP server supports Prometheus HTTP config files to connect to secured Prometheus instances.
An example config can be found in the examples folder here.
Use the --http.config command-line flag to provide an HTTP configuration file.
Please see Flags for more information.
Securing the MCP Server Endpoints
The MCP server supports Prometheus Web Configuration files files to expose it's endpoints behind optional basic auth and custom TLS configs.
Use the --web.config.file command-line flag to provide an HTTP configuration file.
Please see Flags for more information.
Telemetry
Metrics
Once running, the server exposes Prometheus metrics on the configured listen address and telemetry path (:8080/metrics, by default).
Please see Flags for more information on how to change the listening interface, port, or telemetry path.
Prometheus MCP Server Metrics
| Metric name | Type | Description | Labels |
|---|---|---|---|
prom_mcp_build_info |
Gauge |
A metric with a constant '1' value with labels for version, commit and build_date from which prometheus-mcp-server was built. | version, commit, build_date, goversion |
prom_mcp_server_ready |
Gauge |
Info metric with a static '1' if the MCP server is ready, and '0' otherwise. | |
prom_mcp_api_calls_failed_total |
Counter |
Total number of Prometheus API failures, per endpoint. | target_path |
prom_mcp_api_call_duration_seconds |
Histogram |
Duration of Prometheus API calls, per endpoint, in seconds. | target_path |
prom_mcp_tool_calls_failed_total |
Counter |
Total number of failures per tool. | tool_name |
prom_mcp_tool_call_duration_seconds |
Histogram |
Duration of tool calls, per tool, in seconds. | tool_name |
prom_mcp_resource_calls_failed_total |
Counter |
Total number of failures per resource. | resource_uri |
prom_mcp_resource_call_duration_seconds |
Histogram |
Duration of resource calls, per resource, in seconds. | resource_uri |
prom_mcp_docs_last_update_timestamp_seconds |
Gauge |
Unix timestamp of last successful docs auto-update. | |
prom_mcp_docs_update_failures_total |
Counter |
Total number of docs auto-update failures. | |
go_* |
Gauge/Counter |
Standard Go runtime metrics from the client_golang library. |
|
process_* |
Gauge/Counter |
Standard process metrics from the client_golang library. |
Grafana Dashboard
A pre-built Grafana dashboard is included in the grafana/ directory for visualizing the metrics exposed by the MCP server. Import the dashboard json into grafana and it should be ready to go.
Logs
This project makes heavy use of structured, leveled logging.
Please see Flags for more information on how to set the log format, level, and optional file.
Development
Development Environment with Devbox + Direnv
If you use Devbox and
Direnv, then simply entering the directory for the repo
should set up the needed software.
Local LLM with Ollama
See mcp.json for an example MCP config for use with tooling.
Requires ollama to be installed.
NOTE:
To override the default LLM (
ollama:gpt-oss:20b), runexport OLLAMA_MODEL="ollama:your_model"to override it before runningmake.
Using MCP Inspector and a local ollama instance:
Requires MCP Inpsector to be installed:
make inspector
Gemini with gemini-cli
See settings.json for an example config file to run gemini-cli with the prometheus-mcp-server.
Requires gemini-cli to be installed.
Using `gemini-cli` and hosted models:
make gemini
Manual Setup
Required software:
- Working Go environment
- Docker for local tests/linting/image building/etc
- GNU Make
- ollama
- mcp inspector
- mcphost
Building
This project uses the standard Prometheus build tooling: promu
driven through Makefile / Makefile.common. The binary embeds a pinned
snapshot of prometheus/docs, which the build targets download and extract
automatically (the pin lives in DOCS_VERSION in the Makefile).
make build # build the binary for the host platform (via promu)
make test # run the test suite
make crossbuild # build binaries for all release platforms
make # run the full check suite: style, license, yamllint, lint, build, test
Project-specific helper targets (helm packaging and the local LLM client
integrations) are listed by make help:
make help
Usage:
make <target>
Project targets:
help print this help message (see Makefile.common for the standard prometheus targets)
docs download and extract the pinned prometheus/docs snapshot for embedding
helm-sync-dashboards copy grafana dashboards into helm chart for packaging
helm-lint run helm chart linting
helm-template render helm templates for inspection
helm-test install helm chart and run tests (requires a running cluster)
mcphost use mcphost to run the prometheus-mcp-server against a local ollama model
inspector use inspector to run the prometheus-mcp-server in STDIO transport mode
inspector-http use inspector to run the prometheus-mcp-server in streamable HTTP transport mode
open-webui use open-webui to run the prometheus-mcp-server
gemini use gemini-cli to run the prometheus-mcp-server against Google Gemini models
Command Line Flags
The available command line flags are documented in the help flag:
~/go/src/github.com/tjhop/prometheus-mcp-server (main [ ]) -> ./prometheus-mcp-server --help
usage: prometheus-mcp-server [<flags>]
Flags:
-h, --[no-]help Show context-sensitive help (also
try --help-long and --help-man).
($PROMETHEUS_MCP_SERVER_HELP)
--mcp.tools=all ... List of mcp tools to load. The target
`all` can be used to load all tools.
The target `core` loads only the core tools:
docs_list,docs_read,docs_search,runbooks_list,runbooks_read,query,range_query,metric_metadata,label_names,label_values,series
Otherwise, it is treated as an allow-list
of tools to load, in addition to the core
tools. Please see project README for more
information and the full list of tools.
($PROMETHEUS_MCP_SERVER_MCP_TOOLS)
--[no-]mcp.enable-toon-output
Enable Token-Oriented Object Notation
(TOON) output for tools instead of JSON
($PROMETHEUS_MCP_SERVER_MCP_ENABLE_TOON_OUTPUT)
--[no-]mcp.enable-client-logging
Enable sending log messages to connected
MCP clients as protocol notifications.
When enabled, tool execution logs are
sent both to the server's primary
log output and to the MCP client,
allowing LLMs to observe server activity.
($PROMETHEUS_MCP_SERVER_MCP_ENABLE_CLIENT_LOGGING)
--mcp.transport="stdio" The type of transport to use for
the MCP server [`stdio`, `http`].
($PROMETHEUS_MCP_SERVER_MCP_TRANSPORT)
--prometheus.backend=PROMETHEUS.BACKEND
Customize the toolset for a specific
Prometheus API compatible backend.
Supported backends include: prometheus,thanos
($PROMETHEUS_MCP_SERVER_PROMETHEUS_BACKEND)
--prometheus.url="http://127.0.0.1:9090"
URL of the Prometheus instance to connect to
($PROMETHEUS_MCP_SERVER_PROMETHEUS_URL)
--prometheus.timeout=1m Timeout for API calls to the Prometheus backend
($PROMETHEUS_MCP_SERVER_PROMETHEUS_TIMEOUT)
--prometheus.truncation-limit=0
If enabled, this controls the maximum query
response size in number of lines/entries
provided to the LLM from the API response.
LLMs can override truncation limits if
needed on a per-tool-call basis via tool
request arguments on supported tools.
To disable truncation limits, set to 0.
($PROMETHEUS_MCP_SERVER_PROMETHEUS_TRUNCATION_LIMIT)
--http.config=HTTP.CONFIG Path to config file to set
Prometheus HTTP client options
($PROMETHEUS_MCP_SERVER_HTTP_CONFIG)
--web.telemetry-path="/metrics"
Path under which to expose metrics.
($PROMETHEUS_MCP_SERVER_WEB_TELEMETRY_PATH)
--web.max-requests=40 Maximum number of parallel scrape
requests. Use 0 to disable.
($PROMETHEUS_MCP_SERVER_WEB_MAX_REQUESTS)
--[no-]dangerous.enable-tsdb-admin-tools
Enable and allow using tools that access
Prometheus' TSDB Admin API endpoints
(`snapshot`, `delete_series`, and
`clean_tombstones` tools). This is dangerous,
and allows for destructive operations
like deleting data. It is not the fault
of this MCP server if the LLM you're
connected to nukes all your data. Docs:
https://prometheus.io/docs/prometheus/latest/querying/api/#tsdb-admin-apis
($PROMETHEUS_MCP_SERVER_DANGEROUS_ENABLE_TSDB_ADMIN_TOOLS)
--[no-]docs.auto-update Enable automatic documentation updates
from the official prometheus/docs
repository. Checks every 24h0m0s.
($PROMETHEUS_MCP_SERVER_DOCS_AUTO_UPDATE)
--log.file=LOG.FILE The name of the file to log to (file
rotation policies should be configured
with external tools like logrotate)
($PROMETHEUS_MCP_SERVER_LOG_FILE)
--[no-]web.systemd-socket Use systemd socket activation listeners
instead of port listeners (Linux only).
($PROMETHEUS_MCP_SERVER_WEB_SYSTEMD_SOCKET)
--web.listen-address=:8080 ...
Addresses on which to expose metrics and
web interface. Repeatable for multiple
addresses. Examples: `:9100` or `[::1]:9100`
for http, `vsock://:9100` for vsock
($PROMETHEUS_MCP_SERVER_WEB_LISTEN_ADDRESS)
--web.config.file="" Path to configuration file that can
enable TLS or authentication. See:
https://github.com/prometheus/exporter-toolkit/blob/master/docs/web-configuration.md
($PROMETHEUS_MCP_SERVER_WEB_CONFIG_FILE)
--log.level=info Only log messages with the given severity
or above. One of: [debug, info, warn, error]
($PROMETHEUS_MCP_SERVER_LOG_LEVEL)
--log.format=logfmt Output format of log messages. One of: [logfmt,
json] ($PROMETHEUS_MCP_SERVER_LOG_FORMAT)
--[no-]version Show application version.
($PROMETHEUS_MCP_SERVER_VERSION)
FAQ
Common questions
Discussion
Questions & comments · 0
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