Week 6: MCP study-coach server and OpenRouter agent demo#1204
Open
Sheriff10 wants to merge 1 commit intoed-donner:mainfrom
Open
Week 6: MCP study-coach server and OpenRouter agent demo#1204Sheriff10 wants to merge 1 commit intoed-donner:mainfrom
Sheriff10 wants to merge 1 commit intoed-donner:mainfrom
Conversation
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
1 participant
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
This is a small Model Context Protocol (MCP) demo: a Python FastMCP server (study_server.py) exposes two tools list and read Markdown study notes (.md files) that sit in the same folder as the server. A Jupyter notebook (week6-exercise.ipynb) uses the OpenAI Agents SDK to spawn that server over stdio (MCPServerStdio), wires it to an Agent, and runs a natural-language request through Runner.run. The LLM is reached via OpenRouter (OpenAI-compatible API) using OPENROUTER_API_KEY, not the OpenAI platform directly.
Included sample notes (mcp_basics.md, agents_sdk.md) are plain content the agent can retrieve through the tools so you can see tool listing → tool calls → grounded answer end to end. Everything for this exercise lives under 6_mcp/IbrahimSheriff/ (a few files, no extra subfolders for notes).
Trace:
Result:
@hopeogbons