A
licenseNot graded
qualityD
maintenanceMCP server that enables AI coding agents to communicate, share state, and coordinate work in real time via MCP tools or REST API.
123 npm
5
MIT
mirofish-mcp-server
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TDQS
B3.1/5.0
Scored across 50 tools
Disambiguation2/5
Several tools have overlapping purposes, especially around status/progress monitoring: get_task, prepare_status, report_generate_status, get_report_progress, simulation_run_status, and check_report_status all serve similar roles with subtle differences. This makes it difficult for an agent to know which tool to call, leading to potential misselection.
Naming Consistency3/5
All tools share the 'mirofish_' prefix, which is good for namespacing, but the pattern after the prefix is inconsistent. Some tools use verb_noun (get_simulation, list_projects), others use noun_verb (report_generate_status), and a few are noun_noun phrases (simulation_run_status, simulation_history). This mixed style reduces predictability.
Tool Count2/5
With 50 tools, the server is far above the typical well-scoped range. Many tools are redundant (e.g., multiple report progress/status tools, several simulation status variants), making the surface area heavy and harder to navigate. The count should be reduced by consolidating related operations.
Completeness4/5
The tool set covers the main workflow comprehensively: project creation, ontology generation, graph building, simulation lifecycle, agent interviews, and report generation. Minor gaps exist, such as no update_project, no update_simulation_config, and no pause/resume for simulations, but these are not critical given the breadth of coverage.
Maintenance
ActivityInactive
ResponsivenessNo issues