Skip to main content

Maintain a local, LLM-queryable corpus of an IETF Working Group's public record (drafts, mailing list, GitHub issues, meetings), with an MCP server, semantic search, and NotebookLM export.

Project description

ietf-llm

Maintain a local, queryable corpus of an IETF effort's public record — a Working Group, an IRTF Research Group, a mailing list, or a set of drafts. It pulls together charter, drafts, RFCs, meeting agendas, minutes, slides, transcripts, attendance, mailing list archives, and GitHub issues for use with LLM-based tools.

What it's for

A working group's history is spread across mailing list archives, Datatracker, GitHub, and meeting materials — too much to hold in your head, and too scattered to search well by hand. With the record gathered into one queryable corpus, an LLM can help you:

  • Get up to date with the state of discussions — what's open, what was recently decided, where a debate currently stands.
  • Summarise the arguments already made about an issue — every distinct position on a topic, who holds it, and how the chairs ruled.
  • Formulate a new proposal — surface the objections raised against similar ideas before, so you can anticipate them.
  • Fact-check assertions about what's happened so far — grounded in the actual list traffic and chair statements, not someone's recollection.

Tip: for an IRTF Research Group, pass its shortname (e.g. cfrg, hrpc, pearg) wherever the docs use <name> — it works the same as a WG.

Modes of operation

There are three supported workflows:

  1. Use it as an MCP server — register it with Claude, Codex, Cursor, Gemini, Zed, etc. and ask questions across any corpus you've gathered. Two ways to run it:
    • Local MCP — one server subprocess per client, on your own machine. <-- Best starting point
    • As a shared HTTP MCP server — one process serving many concurrent clients (hosted).
  2. Use it from the CLI — run semantic search over the cache directly with ietf-llm-search, no LLM client required.

See the workflow documentation linked above for installation and use instructions, or the full documentation listing.

All three read a corpus you first gather with ietf-llm <corpus>.

Heads up — gathering reaches the network by default. To make a first gather fast, ietf-llm pulls a prebuilt snapshot of covered corpora from the public seed store at seed-store.mnot.net (and list_corpora looks its catalog up there), then freshens only the delta — skipping most of the embedding and download cost. To turn this off: ietf-llm <corpus> --no-seed (it persists across gathers; re-enable with --seed), or set IETF_LLM_SEED_ENABLED=off (or IETF_LLM_SEED_URL=off) in your environment. With seeding off, gathers run fully cold and offline. It is best-effort either way — an unreachable or unlisted corpus just gathers from scratch.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

ietf_llm-0.17.4.tar.gz (757.8 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

ietf_llm-0.17.4-py3-none-any.whl (589.3 kB view details)

Uploaded Python 3

File details

Details for the file ietf_llm-0.17.4.tar.gz.

File metadata

  • Download URL: ietf_llm-0.17.4.tar.gz
  • Upload date:
  • Size: 757.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.14

File hashes

Hashes for ietf_llm-0.17.4.tar.gz
Algorithm Hash digest
SHA256 c67771d3c27f2e897dd6a518816d08f235e1db0322cdd547af7521c5c75803cf
MD5 af0d8dea675bfbeb2b54c07c9c32a25a
BLAKE2b-256 e5a0e2b814644ed0fe3304bc464cc7da1f2ea2a1d7d03bedb82e46d09556a8f4

See more details on using hashes here.

Provenance

The following attestation bundles were made for ietf_llm-0.17.4.tar.gz:

Publisher: publish.yml on mnot/ietf-llm

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file ietf_llm-0.17.4-py3-none-any.whl.

File metadata

  • Download URL: ietf_llm-0.17.4-py3-none-any.whl
  • Upload date:
  • Size: 589.3 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.14

File hashes

Hashes for ietf_llm-0.17.4-py3-none-any.whl
Algorithm Hash digest
SHA256 745b7ddff77adfdd54453dfafdcfd848a5070e7023d96d0927ed5e4098c313fe
MD5 d4cba83c8146e707bb35e15bc75d93ed
BLAKE2b-256 a62868affc529dc75de53f9dbc310a896472c37dde422c10d6e43befe65798cb

See more details on using hashes here.

Provenance

The following attestation bundles were made for ietf_llm-0.17.4-py3-none-any.whl:

Publisher: publish.yml on mnot/ietf-llm

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page