aistarter-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| start_sessionA | Begin a new guided project session. Classifies the user (experience level, then which AI coding tool they're using) and returns the first interview question. Call this before anything else. |
| answer_questionA | Record the human's answer to the current interview question and get the next one. Once all questions are answered, the session moves to the scoping stage. |
| get_sessionB | Fetch the full state of a session: classification, interview answers, and any decisions made so far. |
| list_sessionsA | List every saved session (most recently updated first), so a session can be found again without remembering its id. |
| evaluate_project_scopeA | Draft or finalize the project's scope. Without finalize, returns a heuristic guess at the scope from the interview answers. With finalize: true and data, stores the human-confirmed scope and advances the session. |
| propose_architectureA | Draft or finalize the tech stack. Without finalize, returns a rule-based suggestion (frontend/backend/database/hosting + rationale) based on the finalized scope and the human's experience level. With finalize: true and data, stores the chosen stack. |
| generate_database_schemaA | Draft or finalize a baseline database schema. Without finalize, returns starter collections/tables and a security-rules note picked from the scope. With finalize: true and data, stores the schema. |
| generate_roadmapA | Draft or finalize a sprint-by-sprint roadmap. Without finalize, returns a sprint breakdown sized to the feature set and experience level. With finalize: true and data, stores the roadmap and completes the session. |
| scaffold_project_docsA | Write PROJECT.md, ENVIRONMENT.md, PROGRESS.md, and BUGS_AND_FIXES.md into a target project directory, filled in from a finished session's scope/architecture/schema/roadmap. Call this once, right after generate_roadmap finalizes, at the point where the human is about to start actually implementing the project. |
| check_driftA | Compare a project's actual state (PROGRESS.md checkboxes and package.json dependencies in target_dir) against the finalized scope and architecture from a session. Flags installed libraries that contradict the scope (e.g. a payment library when scope said no payments), stack pieces from the architecture that aren't installed yet, and planned features that don't appear in any roadmap sprint. Call this periodically during implementation, not just once at the start. |
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 10 tools
Each tool maps to a distinct step or artifact in the guided project workflow: session lifecycle, interview, scope, architecture, schema, roadmap, docs, and drift checking. The draft/finalize pattern repeats across four tools but each targets a different deliverable, so there is no real confusion.
Tool names consistently follow a verb_noun pattern: start_session, answer_question, get_session, list_sessions, evaluate_project_scope, propose_architecture, generate_database_schema, generate_roadmap, scaffold_project_docs, check_drift. The two generate_ tools are parallel and unsurprising given they both produce artifacts.
Ten tools is well-scoped for the guided project workflow the server covers. Each tool earns its place in the pipeline, and there is no obvious redundancy or bloat.
The server covers the full journey from initial classification through interview, scope, architecture, schema, roadmap, documentation scaffolding, and ongoing drift checking. The only notable gaps are lifecycle management conveniences like deleting or restarting a session, and there is no explicit tool for revising finalized artifacts after the session completes.