
Interview Mode
io.github.teabagkimPublished by GitHub account teabagkimv0.5.1Updated Oct 24, 2026
Structured interviewer for Claude Code — probing questions, decision tracking, evolving checkpoints.
Overview
A local MCP server that turns Claude Code into a structured interviewer, tracking questions, decisions and evolving checkpoints per topic category.
- What you can do
- Run and manage interviews: start a session with scored checkpoints and a recommended path, then end it to upload metadata and evolve the checkpoint system. Record questions, answers and decisions with checkpoint coverage tracking. Review progress and see uncovered checkpoints ranked by score. Checkpoints are discovered, scored and ranked across sessions per category, with concurrent sessions supported.
- When to use it
- Useful when you want Claude to lead a structured discovery conversation — for example pricing strategy, API design or product decisions — and to keep a record of decisions while reusing topic checklists that improve over repeated sessions.
- Requirements
- Runs locally via npx or a global npm install (Node.js required) and is configured in Claude Code's .mcp.json over stdio. Works out of the box against a shared community Supabase database; optionally set SUPABASE_URL and SUPABASE_ANON_KEY to use your own Supabase project and run the provided schema. Network access is needed for the shared database.
Installation
In SourceWeft
- Open Interview Mode in the dashboard and add it to a workspace.
- Enable the server for the chats that should use its tools.
Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.
Other MCP clients
Follow the launch instructions in the repository.
README
claude-interview-mode
An MCP server that turns Claude into a structured interviewer — and gets smarter with every conversation. Each interview feeds a shared evolution system where checkpoints are scored, ranked, and recommended based on real usage patterns across all users.
The Evolution System
This isn't just an interview tool. It's a collectively evolving knowledge system.
Every time anyone runs an interview in a category (e.g., "saas-pricing"), the system learns:
How evolution works
1. Checkpoint Discovery — When a decision is made during an interview, its topic is automatically registered as a new checkpoint. After just a few sessions, the system knows what topics matter for each category.
2. Bayesian Scoring — Each checkpoint tracks how often it's covered and how often it leads to a decision. The score uses Bayesian smoothing to handle sparse data:
The prior (0.6/2 = 30% base rate) ensures new checkpoints start with a reasonable score. After ~5 sessions, real data dominates.
3. Composite Ranking — Checkpoints are ranked by a composite score combining decision-leading effectiveness (70%) and usage frequency (30%):
High-scoring checkpoints are the ones that consistently lead to concrete decisions — not just topics that get discussed.
4. Recommended Path — The system computes an optimal interview path: checkpoints with decision_rate > 0.2, sorted by their average position in past sessions. This tells Claude not just what to ask, but when to ask it.
5. Community Evolution — All metadata flows to a shared database. When you interview about "api-design", you benefit from every other user who interviewed about "api-design" before you. The checkpoints, scores, and paths evolve collectively.
What gets shared (and what doesn't)
What it does
- Claude drives the interview — asks questions, proposes options with reasoning, challenges assumptions
- Tracks Q&As and decisions — structured records with timestamps
- Evolving checkpoints — learns what topics matter per category, ranked by Bayesian effectiveness scores
- Recommended paths — suggests the optimal order to explore topics based on past interview patterns
- Concurrent sessions — supports multiple interviews running in parallel
- Privacy-first — only anonymous metadata (categories, checkpoint names, counts) goes to the shared database
Install
Or install globally:
Setup with Claude Code
Add to your project's .mcp.json:
Restart your Claude Code session to load the MCP server. That's it — the evolution system starts working immediately via a shared community database.
Optional: Your own Supabase
By default, checkpoint data is stored in a shared community Supabase instance. If you want your own private database:
Then run supabase/schema.sql in your Supabase SQL Editor to create the tables.
Usage
Start an interview with Claude Code:
Claude will lead the conversation. As the interview progresses:
- Each Q&A and decision is recorded with checkpoint coverage
- At the end, metadata is uploaded to evolve the system
- Next time anyone interviews in the same category, the improved checkpoints are loaded
Tools
Architecture
4 database tables power the evolution:
Security:
- Anon key is read-only (SELECT only via RLS)
- All writes go through an Edge Function with input validation and spam defense
- Empty interviews, implausible rates, and oversized payloads are rejected
Development
License
MIT
Source: README.md at commit 8c3c3b2
Tools
0Version history
1- v0.5.1LatestSep 16, 2026
Score
50% of the applicable checks met
How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.
- Reached in the last 30 days25 pts
Keep the endpoint answering the MCP handshake; SourceWeft probes it every 30 days.
- Auth declared10 pts
Declare the credential headers in the registry entry, or keep the endpoint answering the probe so its auth can be classified.
- Tools listed15 pts
Answer tools/list without a credential, or ship a package that starts in a sandbox without one.
- DescriptionRequired15 pts
- Logo10 pts
- Documentation15 pts
- License10 pts
