Obsidian Learning System

i'm working on learning ML compilers + some os concepts this summer so i set up an obsidian vault to track my learning

coincidentally i also wanted some more experience working with mcp so im gonna create an mcp server that connects to codex and gives it some pointers on how to evaluate my learning + make sure my projects are on the right track

stay tuned for updates! we're just getting started ☺︎

Roadmap

This project is a local MCP server for turning an Obsidian vault into a structured compiler-learning interface.

The goal is not just "AI can read my notes."
The goal is to build a real MCP-native learning system with:

• tools for computation and analysis
• resources for stable context surfaces
• prompts for reusable workflows

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Current State

Phase 1 — Existing MCP integration

• Connect Codex to an existing Obsidian MCP server
• Validate basic vault access and note summarization

Phase 2 — Custom local MCP server

• Build a custom Python MCP server
• Expose initial tools:
  • extract_concepts
  • get_learning_gaps
  • generate_study_session
  • compare_notes_to_project
• Register server in Codex
• Verify with MCP Inspector
• Get working end-to-end local tool calls

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Next Up

Phase 3 — Flesh out the MCP interface

Goal: evolve from "bag of tools" into a real MCP-backed learning interface.

3.1 Resources

Expose stable, inspectable views of the learning system.

Planned resources:

• vault://compiler/concepts
• vault://compiler/gaps
• vault://compiler/recent-notes
• vault://project/alignment
• vault://weekly-review/latest

Why:

• tools are good for actions
• resources are good for persistent context
• this makes the server feel more like a system and less like one-off functions

3.2 Prompts

Add reusable workflow templates directly through MCP.

Planned prompts:

• weekly_learning_review
• generate_study_plan
• notes_vs_project_analysis
• paper_to_implementation_breakdown

Why:

• removes the need to remember good prompt phrasing
• turns repeated workflows into first-class interfaces

3.3 Better analysis heuristics

Upgrade from raw keyword counting to more meaningful note analysis.

Planned improvements:

• frontmatter-aware filtering
• tag-aware concept grouping
• recency-aware analysis
• note depth scoring
• backlinks / note-link graph analysis
• better "shallow vs deep" detection
• concept clustering instead of only exact keyword hits

Why:

• current heuristics are useful but primitive
• this is where the actual intelligence of the server improves

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Phase 4 — Multi-source learning system

Goal: compare and synthesize across more than just markdown notes.

Planned sources:

• Obsidian vault
• local project repo(s)
• paper notes / reading notes
• PDFs or exported paper summaries
• lightweight project tracker / task file

Planned capabilities:

• compare notes to implementation
• compare paper concepts to project gaps
• detect studied-but-not-built topics
• generate implementation ideas from recent learning

Why:

• this is where MCP starts becoming genuinely high leverage
• the server becomes a bridge between learning, planning, and building

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Phase 5 — Codex workflow integration

Goal: make the server easy and natural to use inside daily Codex workflows.

Planned work:

• improve tool naming and descriptions
• make outputs more structured and predictable
• add AGENTS.md guidance for when to use each MCP feature
• add example prompts for each tool/resource/prompt
• reduce need for manual tool invocation phrasing

Why:

• a powerful MCP server is useless if the host/client doesn’t use it well
• ergonomics matter just as much as capabilities

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Future / Stretch Ideas

Sampling

Potential future direction:

• let the server request model-generated synthesis through MCP sampling

Possible use cases:

• auto-generate weekly reviews
• synthesize study guides from grouped notes
• produce concept summaries from note clusters

Note: This is intentionally not a near-term priority.
The server should first have strong tools/resources/prompts before adding more agentic behavior.

Remote / hosted version

Potential future direction:

• move from local stdio server to remote server
• support HTTP transport
• add auth if needed
• support broader clients beyond local Codex usage

Note: This is productization, not the immediate learning goal.

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Immediate Priorities

Priority 1

Implement resources:

• concepts
• gaps
• recent notes digest
• notes/project alignment summary

Priority 2

Implement prompts:

• weekly review
• study session
• notes vs project comparison

Priority 3

Improve heuristics:

• frontmatter and tag support
• recency filters
• better depth scoring

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Guiding Principle

This project should move toward:

a real MCP interface for a compiler-learning workflow

and away from:

a pile of loosely related note-analysis functions

If a new feature does not improve one of these, it probably should not be added:

• learning feedback loops
• study planning
• notes-to-project alignment
• reusable Codex workflows
• structured MCP-native interfaces