Agent Knowledge MCP
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Server capabilities have not been inspected yet.
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| create_snapshotC | Create a snapshot (backup) of Elasticsearch indices with comprehensive options and repository management |
| restore_snapshotC | Restore indices from an Elasticsearch snapshot with comprehensive options and conflict resolution |
| list_snapshotsC | List all snapshots in an Elasticsearch repository with detailed information and status |
| create_index_metadataB | Create metadata documentation for an Elasticsearch index to ensure proper governance and documentation |
| update_index_metadataB | Update existing metadata documentation for an Elasticsearch index |
| delete_index_metadataB | Delete metadata documentation for an Elasticsearch index |
| delete_documentB | Delete a document from Elasticsearch index by document ID |
| get_documentA | Retrieve a specific document from Elasticsearch index by document ID |
| index_documentA | Index a document into Elasticsearch with smart duplicate prevention and intelligent document ID generation. 💡 RECOMMENDED: Use 'create_document_template' tool first to generate a proper document structure and avoid validation errors. |
| validate_document_schemaB | Validate document structure against knowledge base schema and provide formatting guidance |
| create_document_templateC | Create a properly structured document template for knowledge base with AI-generated metadata and formatting |
| create_indexB | Create a new Elasticsearch index with optional mapping and settings configuration |
| delete_indexA | Delete an Elasticsearch index and all its documents permanently |
| list_indicesA | List all available Elasticsearch indices with document count and size statistics |
| searchC | Search documents in Elasticsearch index with advanced filtering, pagination, and time-based sorting capabilities |
| batch_index_directoryA | Batch index all documents from a directory into Elasticsearch with AI-enhanced metadata generation and comprehensive file processing |
| get_configB | Get the complete configuration from config.json file with formatted display |
| update_configB | Update configuration with section-specific changes or full configuration replacement |
| validate_configB | Validate configuration object structure, types, and values with comprehensive error reporting |
| reload_configB | Reload configuration from config.json file and reinitialize all components with updated settings |
| setup_elasticsearchB | Auto-setup Elasticsearch using Docker with optional Kibana and force recreate options |
| elasticsearch_statusB | Check status of Elasticsearch and Kibana containers with detailed configuration information |
| server_statusB | Check current server status, version, and available updates with comprehensive system information |
| server_upgradeA | Upgrade this MCP server when installed via uvx with automatic configuration backup and restoration |
| ask_user_adviceA | Ask user for advice when agent encounters uncertainty, problems, or needs guidance. Use this when you're unsure about something or need human input to proceed properly. |
| reset_configA | Reset config.json to defaults from config.default.json (manual reset - overwrites current config) |
| ask_mcp_adviceC | Advanced project guidance using AI-filtered knowledge from .knowledges directory |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
| copilot_instructions | AI Assistant instructions for optimal AgentKnowledgeMCP usage - Complete behavioral guidelines and mandatory protocols |
| smart_prompting_assistant | Smart prompting assistant for managing project workflows, rules, and memories in .knowledges directory |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 27 tools
Most tools have distinct purposes, but some overlap exists. For example, 'ask_mcp_advice' and 'ask_user_advice' both involve seeking guidance, which could cause confusion. However, their descriptions clarify that one uses AI-filtered knowledge and the other involves human input, helping to differentiate them. Overall, the tools are well-defined with minimal ambiguity.
Tool names follow a consistent snake_case pattern with clear verb_noun structures, such as 'create_document_template', 'delete_index', and 'validate_config'. There are no deviations in naming conventions, making the set predictable and easy to understand. This consistency aids in agent selection and reduces confusion.
With 27 tools, the count is borderline high for an MCP server focused on Elasticsearch and knowledge management. While it covers many operations, it may feel heavy and could overwhelm agents. A more streamlined set of 15-20 tools might be more appropriate, but the current scope is still manageable given the domain's complexity.
The tool surface provides comprehensive coverage for Elasticsearch operations and knowledge base management, including CRUD for documents and indices, configuration handling, backup/restore, and validation. There are no obvious gaps; agents can perform full lifecycle management, from setup to maintenance, without encountering dead ends.