About VictoriaMetrics MCP Server
VictoriaMetrics MCP Server exposes metric ingestion and query operations to MCP clients for working with time-series data. It supports Prometheus-format imports, PromQL queries, and label lookup.
Key features
- 01Write metric data
- 02Import Prometheus exposition data
- 03Query time series over a time range
- 04Query current time-series values
- 05Retrieve label names and values
Use cases
- 01Send metrics to VictoriaMetrics
- 02Import metrics in Prometheus exposition format
- 03Analyze time-ranged data with PromQL
- 04Inspect metric labels and their values
MCP support
This MCP server exposes VictoriaMetrics tools for writing data, querying series, and retrieving labels to MCP clients.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEVictoriaMetrics MCP Server
MCP Server for the VictoriaMetrics.
Installing via Smithery
To install VictoriaMetrics Server for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install @yincongcyincong/victoriametrics-mcp-server --client claude
Debug
npx @modelcontextprotocol/inspector -e VM_URL=http://127.0.0.1:8428 node src/index.js
NPX
{
"mcpServers": {
"victoriametrics": {
"command": "npx",
"args": [
"-y",
"@yincongcyincong/victoriametrics-mcp-server"
],
"env": {
"VM_URL": "",
"VM_SELECT_URL": "",
"VM_INSERT_URL": ""
}
}
}
}
📊 VictoriaMetrics Tools API Documentation
1. vm_data_write
Description: Write data to the VictoriaMetrics database.
Input Parameters:
| Parameter | Type | Description | Required |
|---|---|---|---|
metric | object | Tags of the metric | ✅ |
values | number[] | Array of metric values | ✅ |
timestamps | number[] | Array of timestamps in Unix seconds | ✅ |
2. vm_prometheus_write
Description: Import Prometheus exposition format data into VictoriaMetrics.
Input Parameters:
| Parameter | Type | Description | Required |
|---|---|---|---|
data | string | Metrics in Prometheus exposition format | ✅ |
3. vm_query_range
Description: Query time series data over a specific time range.
Input Parameters:
| Parameter | Type | Description | Required |
|---|---|---|---|
query | string | PromQL expression | ✅ |
start | number | Start timestamp in Unix seconds | ⛔️ |
end | number | End timestamp in Unix seconds | ⛔️ |
step | string | Query resolution step width (e.g., 10s, 1m) | ⛔️ |
Only
queryis required; the other fields are optional.
4. vm_query
Description: Query the current value of a time series.
Input Parameters:
| Parameter | Type | Description | Required |
|---|---|---|---|
query | string | PromQL expression to evaluate | ✅ |
time | number | Evaluation timestamp in Unix seconds | ⛔️ |
5. vm_labels
Description: Get all unique label names.
Input Parameters: None
6. vm_label_values
Description: Get all unique values for a specific label.
Input Parameters:
| Parameter | Type | Description | Required |
|---|---|---|---|
label | string | Label name to get values for | ✅ |
Comments
New to MCP?
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An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.
