What can you do with this server?

The Loki MCP Server enables querying and analyzing Grafana Loki logs using LogQL with various capabilities: * Query Loki logs: Submit LogQL queries with optional time ranges, batch size, and limits * Retrieve label information: Get all available labels and their specific values * Multiple output formats: Supports formatted logs, raw logs, and JSON lines format * Authentication: Supports basic auth, bearer tokens and other methods * Flexible configuration: Configure via environment variables or config files * API fallback: Automatically uses Loki HTTP API if logcli is not available

Which integrations are available for this server?

Provides tools for querying Grafana Loki logs using LogQL, accessing label values and metadata, and analyzing log data with support for different output formats and filtering options.

How do I use Loki 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., "@Loki MCP Server show me the last 10 error logs from 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

Loki MCP Server

by ghrud92

Overview Schema Related Servers Score Discussions

TypeScript

Remote

Simple Loki MCP Server

Loki MCP Server is a Model Context Protocol (MCP) interface for querying Grafana Loki logs using logcli. The server enables AI assistants to access and analyze log data from Loki directly.

Features

Query Loki logs with full LogQL support
Get label values and metadata
Authentication and configuration support via environment variables or config files
Provides formatted results in different output formats (default, raw, JSON lines)
Automatic fallback to HTTP API when logcli is not available in the environment

Related MCP server: Loki MCP Server

Prerequisites

Node.js v16 or higher
TypeScript
(Optional) Grafana Loki logcli installed and accessible in your PATH. If logcli is not available, the server will automatically use the Loki HTTP API instead
Access to a Loki server instance

Installation

Installing via Smithery

To install Simple Loki MCP Server for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install @ghrud92/simple-loki-mcp --client claude

for MCP

{
  "mcpServers": {
    "simple-loki": {
      "command": "npx",
      "args": ["-y", "simple-loki-mcp"],
      "env": {
        "LOKI_ADDR": "https://loki.sup.band"
      }
    }
  }
}

npm

Clone the repository:

git clone https://github.com/ghrud92/loki-mcp.git
cd loki-mcp

Install dependencies:

npm install

Build the project:

npm run build

Available MCP Tools

query-loki

Query logs from Loki with filtering options.

Parameters:

query (required): Loki query string (LogQL)
from: Start timestamp (e.g. "2023-01-01T12:00:00Z")
to: End timestamp (e.g. "2023-01-01T13:00:00Z")
limit: Maximum number of logs to return
batch: Batch size for query results
output: Output format ("default", "raw", or "jsonl")
quiet: Suppress query metadata
forward: Display results in chronological order

get-label-values

Retrieve all values for a specific label.

Parameters:

label (required): Label name to get values for

get-labels

Retrieve all available labels.

No parameters required.

Configuration

You can configure Loki access using:

Environment Variables

LOKI_ADDR: Loki server address (URL)
LOKI_USERNAME: Username for basic auth
LOKI_PASSWORD: Password for basic auth
LOKI_TENANT_ID: Tenant ID for multi-tenant Loki
LOKI_BEARER_TOKEN: Bearer token for authentication
LOKI_BEARER_TOKEN_FILE: File containing bearer token
LOKI_CA_FILE: Custom CA file for TLS
LOKI_CERT_FILE: Client certificate file for TLS
LOKI_KEY_FILE: Client key file for TLS
LOKI_ORG_ID: Organization ID for multi-org setups
LOKI_TLS_SKIP_VERIFY: Skip TLS verification ("true" or "false")
LOKI_CONFIG_PATH: Custom path to config file
DEBUG: Enable debug logging

Note: When the client is using the HTTP API mode (when logcli is not available), the same configuration parameters are used to authenticate and connect to the Loki server.

Config Files

Alternatively, create a logcli-config.yaml file in one of these locations:

Custom path specified by LOKI_CONFIG_PATH
Current working directory
Your home directory (~/.logcli-config.yaml)

Example config file:

addr: https://loki.example.com
username: user
password: pass
tenant_id: mytenant

Usage

Start the server:

npm start

For development:

npm run dev

Implementation Details

Automatic Fallback to HTTP API

The server will automatically check if logcli is installed and available in the environment:

If logcli is available, it will be used for all queries, providing the full functionality of the CLI tool
If logcli is not available, the server will automatically fall back to using the Loki HTTP API:
- No additional configuration is needed
- The same authentication parameters are used for the HTTP API
- Response formatting is consistent with the CLI output
- Default limit of 1000 logs per query is applied in both modes

This automatic detection ensures that the server works seamlessly in different environments without manual configuration.

Development

# Run linter
npm run lint

# Fix linting issues
npm run lint:fix

# Run tests
npm run test

License

This project is licensed under the MIT License - see the LICENSE.md file for details.

Available Tools

3 tools

get_labelsD

ParametersJSON Schema

Name	Required	Description	Default
No parameters

TDQS

D1/5.0

Behavior1/5

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

Tool has no description.

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

Conciseness1/5

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

Tool has no description.

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

Completeness1/5

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

Tool has no description.

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?

Tool has no description.

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

Purpose1/5

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

Tool has no description.

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

Usage Guidelines1/5

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

Tool has no description.

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

get_label_valuesD

ParametersJSON Schema

Name	Required	Description	Default
`label`	Yes	Label name to get values for

TDQS

D1/5.0

Behavior1/5

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

Tool has no description.

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

Conciseness1/5

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

Tool has no description.

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

Completeness1/5

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

Tool has no description.

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?

Tool has no description.

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

Purpose1/5

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

Tool has no description.

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

Usage Guidelines1/5

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

Tool has no description.

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

query_lokiD

ParametersJSON Schema

Name	Required	Description
`batch`	No	Batch size for query results
`forward`	No	Display results in chronological order
`from`	No	Start timestamp in UTC (e.g. '2023-01-01T12:00:00Z'). Relative time expressions like '1h ago' are not supported. Use ISO 8601 format.
`limit`	No	Maximum number of logs to return. Maximum value is 1000
`output`	No	Output format - valid values are 'default' (formatted log lines), 'raw' (unprocessed log lines), or 'jsonl' (JSON Lines format). Note: values like 'text' or 'json' are not supported.
`query`	Yes	Loki query string
`quiet`	No	Suppress query metadata
`to`	No	End timestamp in UTC (e.g. '2023-01-01T13:00:00Z'). Relative time expressions like 'now' are not supported. Use ISO 8601 format.

TDQS

D1/5.0

Behavior1/5

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

Tool has no description.

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

Conciseness1/5

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

Tool has no description.

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

Completeness1/5

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

Tool has no description.

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?

Tool has no description.

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

Purpose1/5

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

Tool has no description.

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

Usage Guidelines1/5

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

Tool has no description.

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

Install Server

RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

TDQS

D1.8/5.0

Disambiguation5/5

Each tool has a clearly distinct purpose: get_labels retrieves label names, get_label_values fetches values for a specific label, and query_loki performs log queries. There is no overlap or ambiguity between these functions.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern with snake_case (get_labels, get_label_values, query_loki). The naming is predictable and uniform throughout the set.

Tool Count3/5

With only 3 tools, the set feels thin for a Loki server, which typically handles log management and querying. While the tools cover basic operations, more functionality (e.g., log ingestion, stream management) might be expected.

Completeness2/5

The tool surface is severely incomplete for a Loki server. It lacks essential operations like pushing logs, managing log streams, configuring settings, or performing advanced queries, leaving significant gaps that could cause agent failures.

Maintenance

ActivityInactive

ResponsivenessUnresponsive

Resources

Need Help?

Reddit Discussion

Related Servers

Unclaimed servers have limited discoverability.

Looking for Admin?

If you are the server author, to access and configure the admin panel.

Related MCP Connectors

Foam Observability
io.github.foam-ai
Query application logs, traces, and metrics from your AI coding assistant via Foam's MCP server.
Observability Monitoring Developer Tools
2
Spanly
com.spanly
MCP observability. Query live traffic, errors, duration, and alerts from your AI agent.
Observability Monitoring
3
coralquery-mcp
com.clauxel.coralquery
A paid remote MCP for AI SDK data query MCP, built to return verdicts, receipts, usage logs, and aud
Observability AI & Machine Learning Payments & Billing
2
Grafbase
com.grafbase.api
The Grafbase MCP server sits in front of a GraphQL API and exposes an MCP protocol-compliant interface that allows AI agents and LLMs to explore and query GraphQL APIs using natural language. It provides tools to search schemas, introspect types and fields, and execute GraphQL queries while minimizing context bloat by returning only relevant schema subsets, with built-in support for authentication, authorization, and configurable access control.
API Testing Search Developer Tools
2

Related MCP Servers

Grafana MCP Server
Observability Monitoring
DrDroidLab
A
license
A
quality
D
maintenance
A server that enables AI assistants to access and query Grafana dashboards, metrics, logs, and configurations through an MCP protocol interface.
Updated a year ago (2025-07-24 16:55 UTC)
10
6
MIT
Loki MCP Server
Observability Monitoring
mvs5465-test
F
license
Not graded
quality
D
maintenance
Enables AI models to query and analyze Kubernetes cluster logs through Grafana Loki, supporting semantic operations like error aggregation and pod restart detection. It provides tools for regex-based log searching and namespace discovery to facilitate natural language troubleshooting.
Updated 5 months ago (2026-03-28 00:58 UTC)
grafana-mcp
Monitoring Observability Search
ninanung
A
license
Not graded
quality
D
maintenance
This MCP server enables natural-language querying of Grafana logs by automatically detecting log sources and service labels. It provides read-only access to log data with intelligent caching for efficient repeat queries.
Updated 5 months ago (2026-04-16 01:48 UTC)
35
MIT
loki-mcp-server
Observability Monitoring
mo-silent
F
license
Not graded
quality
F
maintenance
An MCP server that enables AI assistants to query and analyze logs from Grafana Loki using LogQL, supporting label discovery and keyword search.
Updated a year ago (2025-09-15 07:43 UTC)
4

Appeared in Searches

Latest Blog Posts

Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)
By Om-Shree-0709 on July 25, 2026.
mcp
Agent Identity
OAuth 2.1
Your AI Chatbot Just Exposed Your CEO's Salary to an Intern
By Om-Shree-0709 on July 2, 2026.
Agent Identity
MCP Security
OAuth Delegation
Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)
By Om-Shree-0709 on June 30, 2026.
Agentic Ai
Prompt Injection
WebAssembly

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/ghrud92/simple-loki-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server