Skip to main content
Glama
Graphicle-AI

Graphicle MCP Server

Official

Related Servers

Alternatives to Graphicle MCP Server

Related Servers

  • A
    license
    Not graded
    quality
    A
    maintenance
    Enables AI coding agents to query a local structural code graph, inspect code relationships and recorded mistakes, and retrieve focused project context before reading entire files.
    11 npm
    MIT
  • A
    license
    Not graded
    quality
    A
    maintenance
    Enables AI coding agents to retrieve bounded, focused context from a local structural code graph, including source entities, Git relationships, and recorded project memory. It supports exploring structure, inspecting callers, callees, and impact, and carrying prior mistakes into later sessions without reading full files.
    11 npm
    MIT
  • A
    license
    Not graded
    quality
    A
    maintenance
    Provides AI coding agents with token-budgeted, context-aware code retrieval from a persistent code graph, enabling efficient question answering without loading the entire repository.
    Apache 2.0
  • A
    license
    A
    quality
    A
    maintenance
    Provides coding agents with repository-aware tools to understand code structure, find existing patterns, and review plans, architecture, and diffs, enabling a consistent engineering workflow across Cursor, Codex, and Claude Code.
    7
    MIT
  • A
    license
    Not graded
    quality
    C
    maintenance
    Enables AI coding agents to query a pre-built semantic knowledge graph of code, reducing token usage and tool calls. Supports 16 tools for code exploration, analysis, and context building.
    8 npm
    8
    MIT

TDQS

B3.1/5.0

Scored across 22 tools

Disambiguation3/5

Several graph-query tools (query_graph, graph_as_of, get_node, get_neighbors, shortest_path, graph_stats, graph_history_stats, graph_episodes) all retrieve graph information, and memory tools (recall_project, search_project_memory, project_memory, prepare_observations, prepare_memory_refresh) have related search/preparation roles. Descriptions help distinguish temporal vs current, summary vs detail, but an agent can still hesitate between stats variants and memory preparation tools.

Naming Consistency4/5

All names use snake_case, which is consistent and readable. However, the pattern mixes verb_noun (get_node, query_graph, prepare_observations) with noun phrases (god_nodes, graph_stats, project_memory, repository_status), so it is not a uniform verb_noun convention.

Tool Count3/5

22 tools is at the upper end of the moderate range (16-25 feels heavy). The surface covers several subsystems (graph query, memory, source, sessions, workflow), which justifies some breadth, but consolidation of overlapping query/stats tools could reduce the count.

Completeness4/5

The server covers graph querying, temporal episodes, memory reading/search/history, source access, session browsing, and preparation contracts. Minor gaps include no explicit commit/apply tool for prepared memory or observations, and no general repository/project listing, but core workflows appear supported.

Maintenance

ActivityMaintained
ResponsivenessResponsive