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ibm-ecm/ibm-content-services-mcp-server

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The IBM Content Services MCP Server provides a standardized interface that enables IBM FileNet Content Manager (FNCM) capabilities to be used by AI models.

Обзор

The IBM Content Services MCP Server provides a standardized interface that enables IBM FileNet Content Manager (FNCM) capabilities to be used by AI models. The server is available in four specialized configurations to support different workflows: - : Comprehensive document and content management operations - : Document analysis for property extraction and classification - : Legal hold management - : Uses virtual table capabilities for Content Assistant vector search combined with property/metadata search, along with document summarization, comparison, and Q&A Each server can be deployed independently or in combination to support your specific use cases.

README

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Production Warning

  • Do not use in production

IBM Content Services MCP Server

Overview

The IBM Content Services MCP Server provides a standardized interface that enables IBM FileNet Content Manager (FNCM) capabilities to be used by AI models. The server is available in four specialized configurations to support different workflows:

  • Core Server: Comprehensive document and content management operations
  • Property Extraction and Classification Server: Document analysis for property extraction and classification
  • Legal Hold Server: Legal hold management
  • AI Document Insight Server: Uses virtual table capabilities for Content Assistant vector search combined with property/metadata search, along with document summarization, comparison, and Q&A

Each server can be deployed independently or in combination to support your specific use cases.


Server Types and Capabilities

Core Server (core-cs-mcp-server)

Purpose: Comprehensive document and content management operations

Use Cases:

  • General document lifecycle management (create, update, check-in, check-out, delete)
  • Folder operations and document filing
  • Search and retrieval across the repository
  • Metadata and class management
  • Resources support for exposing documents as LLM context

Property Extraction and Classification Server (property-extraction-and-classification-cs-mcp-server)

Purpose: Document analysis for property extraction and classification

Dependencies: Requires Core Server for document update operations (e.g., update_document_properties)

Use Cases:

  • Automated property extraction from document content
  • Document classification and reclassification workflows
  • Content-based metadata enrichment

Legal Hold Server (legal-hold-cs-mcp-server)

Purpose: Legal hold management

Use Cases:

  • Creating and managing legal holds
  • Placing documents and objects under hold
  • Tracking held objects

AI Document Insight Server (ai-document-insight-cs-mcp-server)

Purpose: Uses virtual table capabilities for Content Assistant vector search combined with property/metadata search, along with document summarization, comparison, and Q&A

Dependencies:

  • Requires Core Server for document operations
  • Requires Persistent Text Extract add-on
  • Requires Content Assistant add-on
  • Requires FileNet 5.7.0 IF003 or later

Use Cases:

  • Content-based document search with metadata filtering using Content Assistant API vector search
  • Content Assistant API document summaries
  • Content Assistant API document comparison and analysis

Tools List

Core Server Tools

The Core Server provides 26 tools organized into the following categories:

Document Management (11 tools)

  • get_document_versions: Retrieves a document’s version history, including major and minor version numbers and document IDs for each version.
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Установка

uvx --from git+https://github.com/ibm-ecm/ibm-content-services-mcp-server core-cs-mcp-server
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Конфигурация

{ "mcpServers": { "core-cs-mcp-server": { "command": "/path/to/your/uvx", "args": [ "--from", "/path/to/your/cs-mcp-server", "core-cs-mcp-server" ], "env": { "USERNAME": "your_username", "PASSWORD": "your_password", "SERVER_URL": "https://your-graphql-server/content-services-graphql/graphql", "OBJECT_STORE": "your_object_store" } } } }