Session Buddy
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| PYTHONPATH | No | Path to the session-buddy directory for module resolution |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": true
} |
| logging | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| analyze_codeB | Comprehensive Python code quality analysis with complexity, dead code, clone detection, and coupling metrics |
| check_complexityB | Analyze cyclomatic complexity of Python functions |
| check_couplingA | Analyze class coupling (CBO - Coupling Between Objects) metrics |
| detect_clonesB | Detect code clones using APTED tree edit distance and LSH acceleration |
| find_dead_codeB | Find unreachable code using Control Flow Graph (CFG) analysis |
| get_health_scoreB | Get overall code health score (0-100) with grade and category scores |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 6 tools
The tools have overlapping purposes that could cause confusion, particularly between analyze_code and the more specific tools like check_complexity and check_coupling. While descriptions clarify their focus, an agent might struggle to choose between analyze_code (which includes complexity and coupling) and the dedicated tools, leading to potential misselection.
All tool names follow a consistent verb_noun pattern (e.g., analyze_code, check_complexity, detect_clones), using snake_case throughout. This predictability makes it easy for agents to parse and understand the naming conventions without confusion.
With 6 tools, the count is well-scoped for a code analysis server, covering key aspects like complexity, coupling, clones, and dead code. Each tool appears to earn its place without feeling excessive or insufficient for the domain.
The tool set provides good coverage for code quality analysis, including metrics, clone detection, and dead code. A minor gap exists in areas like code style or security analysis, but agents can likely work around this with the available tools for core workflows.