microsoft / microsoft/mcp-interviewer
✨️ Collaboration: Stress-Testing "Routing Latency" and "Constraint Limits" with WisePick
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 155
- Forks
- 20
- Avg merge
- 21d 23h
- Merged PRs (30d)
- 1
Description
Hi Team,
MCP Interviewer is a vital tool for the ecosystem. You've highlighted key constraints, such as OpenAI's 128-tool limit.
I am building WisePick, which addresses these exact constraints by moving the routing logic outside the LLM context, achieving 0.0s latency and supporting 10,000+ tools.
I’d love to collaborate on adding a "Routing Efficiency" report to MCP Interviewer. We can use WisePick as a benchmark to show how much latency and context budget developers can save by switching from LLM-based tool selection to deterministic routing.
Telegram: @wenjiewu | Email: w2jmoe@gmail.com
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
The issue names no files, tests, or entry points, so first inspect the repository to find how reports, routing, and constraint evaluation are structured. Before implementing anything, define the Routing Efficiency report's scope and acceptance criteria, including how WisePick would benchmark latency and context-budget savings against LLM-based tool selection.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- ai
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Quiet
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100