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Kagan - AI Orchestration Layer

by kagan-sh
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TypeScript
Hybrid

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Deploy Server
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

C2.9/5.0

Scored across 47 tools

Disambiguation2/5

Multiple tools cover near-identical ground: run_start, run_execute, run_status, task_run, and task_wait all relate to task execution with unclear boundaries. fs_read_file, fs_write_file, fs_edit_file, bash_exec, and terminal_exec overlap heavily in file/command operations, requiring deep reading to distinguish.

Naming Consistency2/5

Naming mixes several conventions: verb_noun (task_get, insight_add, fs_read_file), verb-only (run, plan, analyze), and inconsistent grouping (run_status vs run_start vs run_execute). Some tools use nouns (terminal) while others use prefixes (fs_), creating no clear pattern.

Tool Count2/5

47 tools is excessive for a focused orchestration layer, well beyond the 3-15 sweet spot. Many tools could be consolidated (multiple run_* variants, multiple analytics_* tools, multiple fs_* tools), suggesting the surface area was not thoughtfully pruned.

Completeness4/5

Core domain coverage is quite thorough: task lifecycle (create/get/update/delete), execution (run/stop/wait), files (read/write/list), and insights (list/search/remove) are all represented. Minor gaps exist (e.g., no explicit project delete, no user management), but nothing creates a dead end.

Maintenance

ActivitySlowing
ResponsivenessUnresponsive

Resources