IaC Memory MCP Server
Related Servers
Alternatives to IaC Memory MCP Server
No user-submitted related servers found.
Related Servers
AlicenseAqualityCmaintenanceProvides persistent memory for Claude with hierarchical categorization, cross-corpus recall, session journals, and customizable persona, enabling memory continuity across sessions.7MIT- AlicenseNot gradedqualityDmaintenanceProvides Claude with a persistent local memory and structured knowledge graph to track project states, tasks, and historical decisions across different chat sessions. It enables users to recall information using keyword relevance, time-travel queries, and dependency analysis for complex project management.MIT
- AlicenseAqualityCmaintenancePersistent memory and automatic git snapshots for Claude Code, capturing decisions, patterns, and architecture across sessions.1036 npm98MIT
- FlicenseNot gradedqualityDmaintenanceProvides persistent memory capabilities for Claude Code using Neo4j graph database to track development tasks, code patterns, solutions, and their relationships across sessions and projects, enabling contextual assistance and pattern recognition.11-
- FlicenseAqualityDmaintenanceProvides persistent memory, identity, and context for Claude sessions through a memory graph, enabling recall, storage, and relationship management of entities and decisions.8-
- -licenseNot gradedqualityNot gradedmaintenanceProvides Claude Desktop with persistent memory across sessions, storing up to 10,000 memories with semantic search and automatic context bridging. Features temporal versioning and anti-degradation protocols to maintain conversation continuity.-
TDQS
Scored across 23 tools
Most tools have distinct purposes targeting specific IaC components (Ansible vs. Terraform) and operations (add/get/list/update). However, there is some potential overlap between 'create_entity' and the various 'add_' tools, as both involve storing information, though 'create_entity' seems more generic for a knowledge graph. The descriptions help clarify boundaries, but an agent might need to infer when to use 'create_entity' versus the specific 'add_' tools.
Tool names follow a highly consistent verb_noun pattern throughout, with clear and predictable conventions. All tools use snake_case, and verbs like 'add', 'get', 'list', 'update', 'delete', and 'view' are applied consistently across similar resource types (e.g., 'add_ansible_collection', 'get_ansible_collection_info', 'list_ansible_collections'). This makes the tool set easy to navigate and understand.
With 23 tools, the count is on the higher side for an MCP server, bordering on heavy. While the server covers both Ansible and Terraform domains comprehensively, the number of tools might feel overwhelming or lead to redundancy (e.g., separate tools for version history and compatibility checks). A more streamlined set could improve usability without losing functionality, placing it in the borderline range.
The tool surface provides complete CRUD/lifecycle coverage for both Ansible and Terraform components, including adding, retrieving, listing, updating, and deleting entities. It also handles version management, compatibility checks, and relationship viewing for a knowledge graph. No obvious gaps exist; agents can perform all expected operations for managing IaC metadata and entities without dead ends.