The Kibana MCP Server enables MCP-compatible clients to interact with Kibana instances through natural language or programmatic requests, dynamically managing API endpoints based on official Elastic Stack 8.x OpenAPI specifications.
• Connect Securely: Connect to local or remote Kibana instances using username/password authentication with SSL/TLS and custom CA certificate support • Multi-Space Operations: Access and manage APIs across multiple Kibana spaces in enterprise environments • Dynamic API Management: List, search, and get detailed information about Kibana API endpoints using keyword searches or comprehensive listings • Execute Custom Requests: Perform API operations (GET, POST, PUT, DELETE) with custom parameters, bodies, and target spaces • Monitor Server Status: Check Kibana server status globally or for specific spaces • Manage Spaces: Retrieve and manage available Kibana spaces with detailed information • Flexible Integration: Seamlessly integrate with MCP clients like Claude Desktop, supporting both conversational (tool-based) and raw data access (resource-based) interaction modes
Connects to Elastic Stack services through Kibana, using the OpenAPI YAML specification from Elastic Stack 8.x (ES8) to dynamically retrieve and manage all Kibana API endpoints.
Provides access to Kibana instances through API endpoints, allowing users to search, view, and execute Kibana APIs. Supports operations like checking server status, managing saved objects, creating dashboards, handling cases, and accessing endpoint events through Kibana's API.
Click on "Deploy 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., "@Kibana MCP Server show me the top 5 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.
A Kibana MCP server implementation that allows any MCP-compatible client (such as Claude Desktop) to access your Kibana instance via natural language or programmatic requests.
This project is based on the official Elastic Kibana API documentation and uses the OpenAPI YAML specification from Elastic Stack 8.x. For details, see the Kibana API documentation.
This project is community-maintained and is not an official product of Elastic or MCP.
💡 Companion Project: For complete Elastic Stack integration, pair this with Elasticsearch MCP Server for direct Elasticsearch data operations.
# Global installation (recommended)
npm install -g @tocharianou/mcp-server-kibana
# Or use directly with npx
npx @tocharianou/mcp-server-kibanagit clone https://github.com/TocharianOU/mcp-server-kibana.git
cd mcp-server-kibana
npm install && npm run buildRelated MCP server: mshegolev/kibana-mcp
Add to your Claude Desktop configuration file:
MacOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json
{
"mcpServers": {
"kibana": {
"command": "npx",
"args": ["@tocharianou/mcp-server-kibana"],
"env": {
"KIBANA_URL": "http://your-kibana-server:5601",
"KIBANA_API_KEY": "your-api-key",
"KIBANA_DEFAULT_SPACE": "default"
}
}
}
}# Using API Key (recommended)
KIBANA_URL=http://localhost:5601 \
KIBANA_API_KEY=your-api-key \
npx @tocharianou/mcp-server-kibana
# Using Basic Auth
KIBANA_URL=http://localhost:5601 \
KIBANA_USERNAME=your-username \
KIBANA_PASSWORD=your-password \
npx @tocharianou/mcp-server-kibana
# Using Cookie Auth
KIBANA_URL=http://localhost:5601 \
KIBANA_COOKIES="sid=xxx; security-session=yyy" \
npx @tocharianou/mcp-server-kibanaMCP_TRANSPORT=http \
MCP_HTTP_PORT=3000 \
KIBANA_URL=http://localhost:5601 \
KIBANA_API_KEY=your-api-key \
npx @tocharianou/mcp-server-kibanaAccess at: http://localhost:3000/mcp
Health check: http://localhost:3000/health
Dual transport modes: Stdio (local) and HTTP (remote access)
Multiple authentication methods: API Key, Basic Auth, Cookie-based
Multi-space support: Enterprise-ready Kibana space management
SSL/TLS support: Custom CA certificate configuration
Session management: Automatic UUID generation for HTTP mode
Dynamic API discovery: Based on official Kibana OpenAPI specification
Complete CRUD operations for all Kibana saved object types
Intelligent search with pagination support
Bulk operations for efficient mass updates
Version control with optimistic concurrency
Reference management for object relationships
Variable | Description | Example |
| Kibana server address |
|
Variable | Description | Priority |
| API Key (base64 encoded) | 1st |
| Basic authentication | 2nd |
| Session cookies | 3rd |
Variable | Description | Default |
| Default Kibana space |
|
| CA certificate path | - |
| Request timeout (ms) |
|
| Transport mode |
|
| HTTP server port |
|
| HTTP server host |
|
| Disable SSL validation |
|
get_status - Get Kibana server status
execute_kb_api - Execute custom Kibana API requests
get_available_spaces - List available Kibana spaces
search_kibana_api_paths - Search API endpoints
list_all_kibana_api_paths - List all API endpoints
get_kibana_api_detail - Get API endpoint details
vl_search_saved_objects - Search saved objects (universal)
vl_get_saved_object - Get single saved object
vl_create_saved_object - Create new saved object
vl_update_saved_object - Update single saved object
vl_bulk_update_saved_objects - Bulk update operations
vl_bulk_delete_saved_objects - Bulk delete operations
Supported Object Types: dashboard, visualization, index-pattern, search, config, lens, map, tag, canvas-workpad, canvas-element
analyze_object_dependencies - Analyze saved object dependencies
analyze_deletion_impact - Check impact before deletion
check_dashboard_health - Dashboard health check
scan_all_dashboards_health - Batch health scanning
Resource URI | Description |
| List all available API endpoints |
| Search endpoints by keyword |
| Get specific endpoint details |
"What is the status of my Kibana server?"
"List all available Kibana spaces"
"Show me all API endpoints related to dashboards"
"Search for all dashboards"
"Find visualizations containing 'nginx' in the title"
"Create a new dashboard named 'Sales Overview'"
"Update the description of dashboard 'my-dashboard-123'"
"Delete multiple dashboards by their IDs"
"Check health of dashboard 'overview'"
"Analyze dependencies for visualization 'viz-123'"
"Scan all dashboards for health issues"
Verify Kibana URL is accessible
Check authentication credentials
For SSL issues: NODE_TLS_REJECT_UNAUTHORIZED=0 (use with caution)
Restart Claude Desktop after config changes
Validate JSON config syntax
Check console logs for errors
"import: command not found": Update to latest version
Authentication failed: Verify credentials and permissions
SSL errors: Check CA certificate or disable SSL validation
Use MCP Inspector for debugging:
npm run inspectorThis provides a browser-accessible debugging interface.
GitHub: TocharianOU/mcp-server-kibana
Node.js: >= 18.0.0
License: Apache 2.0
This project is community-maintained. Contributions and feedback are welcome!
Please follow the Elastic Community Code of Conduct in all communications.
Apache License 2.0 - See LICENSE file for details.
Execute a custom API request for Kibana with multi-space support
| Name | Required | Description | Default |
|---|---|---|---|
| body | No | ||
| method | Yes | ||
| params | No | ||
| path | Yes | ||
| space | No | Target Kibana space (optional, defaults to configured space) |
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 'multi-space support' which adds some context about space handling, but fails to describe critical behaviors like authentication requirements, rate limits, error handling, or what 'execute' entails (e.g., whether it's idempotent, what happens on failure). For a tool that can perform write operations (PUT, DELETE), this is inadequate.
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 ('Execute a custom API request for Kibana') and adds a key feature ('with multi-space support'). There's no wasted language or 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?
Given the complexity (5 parameters, no output schema, no annotations, and support for write operations), the description is incomplete. It lacks information about return values, error conditions, authentication, and how to use parameters effectively. The mention of 'multi-space support' is helpful but insufficient for a tool with this scope and potential impact.
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 only 20% (only the 'space' parameter has a description), so the description must compensate. It adds minimal value by implying the tool handles 'multi-space' contexts, which relates to the 'space' parameter, but doesn't explain other parameters like 'body', 'params', 'method', or 'path' beyond what the schema provides. The baseline is 3 since schema coverage is low but the description doesn't fully compensate.
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 ('execute') and resource ('custom API request for Kibana'), specifying the action and target. However, it doesn't explicitly differentiate from siblings like 'get_kibana_api_detail' or 'list_all_kibana_api_paths', which appear to be read-only operations, while this tool supports multiple HTTP methods including write operations.
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 mentions 'multi-space support' but doesn't provide explicit guidance on when to use this tool versus alternatives. No context is given about prerequisites, when-not-to-use scenarios, or comparisons to sibling tools like 'get_available_spaces' or 'search_kibana_api_paths'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get all available Kibana spaces with current context
| Name | Required | Description | Default |
|---|---|---|---|
| include_details | No | Include detailed space information (name, description, etc.) |
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 what the tool does but lacks details on permissions needed, rate limits, pagination, or what 'current context' entails. This is a significant gap for a tool that likely interacts with a Kibana API.
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 directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded, making it easy to parse quickly.
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. It doesn't explain what 'available spaces' means, what 'current context' includes, or what the return values look like. For a tool that likely returns a list of Kibana spaces, more context is needed to guide the agent effectively.
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?
The schema description coverage is 100%, so the input schema already documents the 'include_details' parameter. The description doesn't add any parameter-specific information beyond what's in the schema, such as examples or edge cases, but the baseline is 3 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 verb 'Get' and the resource 'all available Kibana spaces with current context', making the purpose understandable. However, it doesn't explicitly differentiate this tool from its siblings like 'list_all_kibana_api_paths' or 'search_kibana_api_paths', which might also involve listing Kibana resources.
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 any prerequisites, exclusions, or compare it to sibling tools like 'list_all_kibana_api_paths', leaving the agent to infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get details for a specific Kibana API endpoint
| Name | Required | Description | Default |
|---|---|---|---|
| method | Yes | HTTP method, e.g. GET, POST, PUT, DELETE | |
| path | Yes | API path, e.g. /api/actions/connector_types |
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 what the tool does but doesn't describe how it behaves—such as whether it's read-only, what format the details are returned in, error handling, or any rate limits. This is a significant gap for a tool with no annotation coverage.
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 directly states the tool's purpose without any fluff. It's appropriately sized and front-loaded, making it easy to parse quickly.
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 querying API endpoints and the lack of annotations and output schema, the description is insufficient. It doesn't explain what 'details' include, how results are structured, or any behavioral aspects like safety or performance, leaving the agent with incomplete information for proper 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?
The schema description coverage is 100%, with both parameters ('method' and 'path') well-documented in the schema. The description adds no additional meaning beyond implying that these parameters identify a specific endpoint, which is already clear from the schema. This meets the baseline for high 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 verb ('Get details') and resource ('specific Kibana API endpoint'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'list_all_kibana_api_paths' or 'search_kibana_api_paths' which also deal with Kibana API endpoints, so it doesn't fully distinguish itself from alternatives.
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_all_kibana_api_paths' or 'execute_kb_api'. It doesn't mention prerequisites, context, or exclusions, leaving the agent to infer usage based on the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get Kibana server status with multi-space support
| Name | Required | Description | Default |
|---|---|---|---|
| space | No | Target Kibana space (optional, defaults to configured space) |
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 states what the tool does but lacks behavioral details: it doesn't specify if this is a read-only operation, what permissions are required, whether it affects system state, rate limits, or what the output format looks like (e.g., JSON structure, error handling). For a 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 a single, efficient sentence that front-loads the core purpose ('Get Kibana server status') and adds a key feature ('with multi-space support'). There is no wasted verbiage, and it's appropriately sized for a simple tool with one optional parameter.
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 low complexity (1 optional parameter, no output schema, no annotations), the description is minimally complete. It covers the basic purpose but lacks context on usage guidelines, behavioral traits, or output details. For a status-checking tool, it should ideally mention what 'status' entails (e.g., health metrics, version info) or how it differs from siblings, but it's adequate as a starting point.
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%, with the single parameter 'space' documented in the schema as optional and defaulting to configured space. The description adds minimal value beyond this by mentioning 'multi-space support', which implies the parameter's purpose but doesn't provide additional syntax or format details. Baseline 3 is appropriate as the schema handles parameter documentation adequately.
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 ('Get') and resource ('Kibana server status'), making the purpose evident. It adds specificity with 'multi-space support' which distinguishes it from generic status tools. However, it doesn't explicitly differentiate from sibling tools like 'get_kibana_api_detail' or 'execute_kb_api', which might also retrieve status-related information.
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 'multi-space support' but doesn't explain if this is for checking overall server health, space-specific status, or when to prefer it over siblings like 'get_available_spaces' or 'execute_kb_api'. No explicit when/when-not instructions or prerequisites are included.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
List all Kibana API endpoints as a resource list
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
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 states what the tool does but doesn't describe important behavioral traits like whether this is a read-only operation, what format the resource list returns, whether there are rate limits, or if authentication is required. The description is functional but lacks operational 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 communicates the core functionality without any wasted words. It's appropriately sized for a zero-parameter tool and front-loads the essential information ('List all Kibana API endpoints').
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 zero-parameter tool with no output schema, the description adequately states what the tool does but lacks important context about the return format, behavioral characteristics, and differentiation from sibling tools. Given the complexity of API endpoint listing and the absence of annotations/output schema, the description should provide more operational guidance to be truly complete.
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?
The tool has 0 parameters with 100% schema description coverage, so the baseline is 4. The description appropriately doesn't discuss parameters since none exist, and the schema fully documents this absence without needing additional explanation in the description.
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 all') and resource ('Kibana API endpoints as a resource list'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'search_kibana_api_paths' or 'get_kibana_api_detail', which would require more specific scope information.
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 'search_kibana_api_paths' or 'get_kibana_api_detail'. There's no mention of use cases, prerequisites, or comparisons with sibling tools, leaving the agent without contextual usage information.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Search Kibana API endpoints by keyword
| Name | Required | Description | Default |
|---|---|---|---|
| search | Yes | Search keyword for filtering API endpoints |
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 searches endpoints by keyword, but doesn't describe behavioral traits such as whether it's read-only, safe to use, what the output format looks like (e.g., list of paths, details), or any limitations (e.g., search scope, rate limits). For a 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: 'Search Kibana API endpoints by keyword'. It's front-loaded with the core action and resource, with zero wasted words. Every part of the sentence earns its place by conveying essential purpose, 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 tool's complexity (a search function with one parameter) and the lack of annotations and output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., a list of endpoint paths, details, or matches), how results are formatted, or any behavioral context needed for effective use. This leaves significant gaps for the agent to understand the tool's full context.
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?
The input schema has 100% description coverage, with the single parameter 'search' documented as 'Search keyword for filtering API endpoints'. The description adds no additional meaning beyond this, as it only repeats the keyword concept without elaborating on syntax, format, or examples. Given the high schema coverage, the 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 tool's purpose: 'Search Kibana API endpoints by keyword'. It specifies the verb ('search'), resource ('Kibana API endpoints'), and mechanism ('by keyword'), which is specific and actionable. However, it doesn't explicitly differentiate from sibling tools like 'list_all_kibana_api_paths' or 'get_kibana_api_detail', which prevents a perfect score.
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 sibling tools like 'list_all_kibana_api_paths' (which might list all endpoints without filtering) or 'get_kibana_api_detail' (which might retrieve details for a specific endpoint), leaving the agent to infer usage context. This lack of explicit when-to-use or alternative references results in minimal guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
v1.0.0execute_kb_apiget_available_spacesget_kibana_api_detailget_statuslist_all_kibana_api_pathssearch_kibana_api_pathsScored across 6 tools
Each tool has a clearly distinct purpose with no overlap: execute_kb_api performs custom API calls, get_available_spaces lists spaces, get_kibana_api_detail provides endpoint details, get_status checks server status, list_all_kibana_api_paths enumerates all endpoints, and search_kibana_api_paths searches endpoints. The descriptions reinforce these unique functions, making misselection unlikely.
All tools follow a consistent verb_noun pattern with snake_case: execute_kb_api, get_available_spaces, get_kibana_api_detail, get_status, list_all_kibana_api_paths, and search_kibana_api_paths. The naming is predictable and readable throughout the set, with no deviations in style or convention.
With 6 tools, the count is well-scoped for a Kibana MCP server focused on API exploration and execution. Each tool earns its place by covering distinct aspects like status, spaces, endpoint listing, searching, detailing, and execution, avoiding bloat while providing comprehensive functionality.
The tool set is highly complete for exploring and interacting with Kibana APIs, covering discovery (list/search), details, spaces, status, and execution. A minor gap exists in lacking direct CRUD operations for Kibana objects like dashboards or visualizations, but agents can work around this using execute_kb_api for custom requests.
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