GID MCP Server
Related Servers
Alternatives to GID MCP Server
No user-submitted related servers found.
Related Servers
- AlicenseNot gradedqualityCmaintenanceTransforms codebases into structural knowledge graphs for AI agents and developers, providing precise architectural awareness and dependency mapping.54MIT
- FlicenseAqualityBmaintenanceEnables AI assistants to deeply understand codebases via Knowledge Graphs, supporting fuzzy search, architecture layer queries, call chain tracing, impact analysis, and domain knowledge with multi-project support.182-
- AlicenseNot gradedqualityCmaintenanceEnables AI agents to query and analyze code across multiple repositories through a unified knowledge graph, with tools for symbol search, impact analysis, and graph algorithms.11 npmMIT
- FlicenseNot gradedqualityDmaintenanceAI-native code intelligence graph that builds a persistent knowledge graph of your codebase in Neo4j and exposes it to AI assistants via MCP, enabling contextual code analysis, impact analysis, and dependency tracking.23-
- AlicenseNot gradedqualityCmaintenanceProvides semantic code search and code insights via a knowledge graph, enabling AI to understand, navigate, and modify complex projects with deep dependency and architecture analysis.MIT
- FlicenseNot gradedqualityAmaintenanceEnables developer agents to perform semantic codebase search, dependency and impact analysis, cross-file refactoring, and full-stack API tracing through a unified query DSL over a high-performance graph engine.-
TDQS
Scored across 20 tools
Each tool has a clear and distinct purpose, with descriptions that differentiate them well. For example, gid_analyze focuses on file/function/class analysis, gid_extract extracts dependency graphs from code, and gid_semantify proposes semantic upgrades. There is no significant overlap.
All tools follow a consistent 'gid_verb_noun' pattern in snake_case. The verbs are imperative and descriptive (e.g., gid_init, gid_query_deps, gid_edit_graph), and there is no mixing of conventions.
With 20 tools, the server covers a broad range of graph management operations. While slightly above the typical 3-15 range, each tool serves a specific function and the count is justified by the comprehensive feature set.
The tool set covers the full lifecycle: initialization, reading, editing, version history, code extraction, analysis, design from requirements, multiple query types (dependencies, impact, path, common cause), task management, and visualization. There are no obvious gaps for the stated domain.