dhruv's obsidian mcp

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

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

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

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

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

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.

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

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