Extracts transcripts from YouTube videos using yt-dlp, whisper, or youtube-transcript-api to generate grounded summaries.
This server does not currently have a deployable release on Glama. Follow the repository's setup instructions to install and configure it for your MCP client, including any required credentials and local dependencies.
Turn a plain list of links (videos, posts, repos, articles) into a verified, browsable knowledge base — and let your AI coding tool enrich it with grounded, hallucination-checked summaries.
It ships three ways to drive the same pipeline so it works with any AI tool:
a CLI (knowledge-forge ...)
an MCP server (knowledge-forge-mcp) for Cursor, Claude Code, Claude Desktop, etc.
portable skills + editor hooks
links.txt ──▶ extract (yt-dlp / whisper / youtube-transcript)
──▶ classify into categories + pull verified learnings
──▶ videos.json ──▶ generate a category/detail canvas (.canvas.tsx)
──▶ [optional] rule-based enrichment + an agent queue
──▶ agent writes 300-1000 word grounded summaries
──▶ validate (anti-hallucination gate) ──▶ apply ──▶ refreshKey idea: summaries are grounded. A validator enforces word count, per-paragraph token overlap with the source material, source-URL provenance, and a no-engagement-bait rule — so the agent can't invent facts, repos, or URLs.
Related MCP server: Lore Agent
pip install "knowledge-forge[all]" # CLI + MCP + extraction + transcription
# or pick extras: .[extract] .[transcribe] .[mcp]Core has no third-party dependencies; the extras add yt-dlp,
youtube-transcript-api, faster-whisper, and mcp.
knowledge-forge init # scaffold config + folders in the current dir
# ... add URLs to links.txt (see samples/links.sample.txt) ...
knowledge-forge update # extract + classify + build the canvas
knowledge-forge run # rule-based enrich + build the agent queue
knowledge-forge queue # see what needs an agent-written summary
# agent writes payload.json, then:
knowledge-forge validate --file payload.json
knowledge-forge apply --file payload.jsonGenerate a one-command launcher for your OS:
knowledge-forge bootstrap --write # writes kf.ps1+kf.bat (Windows) or kf.sh (macOS/Linux)Everything is path-driven via knowledge-forge.json (see config.example.json).
All relative paths resolve against the config file's directory — no machine- or
OS-specific paths are baked in. The config is auto-discovered by walking up from
the CWD, or set KNOWLEDGE_FORGE_PROJECT / KNOWLEDGE_FORGE_CONFIG.
Key | Default | Meaning |
|
| inputs |
|
| the knowledge store |
|
| cached transcripts |
|
| agent work queue |
|
| generated UI |
|
| summary gate |
|
| entries per agent batch |
Tool | MCP | Hooks | Skills |
Cursor |
|
|
|
Claude Code |
| — |
|
any MCP client | run | — | — |
MCP tools: kf_update, kf_refresh, kf_run, kf_queue, kf_list, kf_validate, kf_apply.
See integrations/<tool>/README.md for copy-paste setup.
knowledge_forge/ core package (config, pipeline, classify, verify, enrich, canvas, cli)
mcp_server/ FastMCP stdio server
skills/ tool-agnostic SKILL.md files
integrations/ per-tool hooks + MCP config + setup docs
samples/ anonymized example links + data
config.example.json starter configMIT — see LICENSE.
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Knowledge Network for AI Agents and creators: Search, rate, and review programming guides via MCP
Shared, peer-validated knowledge archive for AI agents — search, contribute, and validate via MCP
Knowledge commons for AI agents: cited, licensed, queryable claims over MCP.
Your memory, everywhere AI goes. Build knowledge once, access it via MCP anywhere.
