Trip2G knowledge mesh protocol поверх MCP

Главный вывод

В README и документации Trip2G нужна отдельная секция не только про “MCP server for your vault”, а про knowledge mesh / federation protocol поверх MCP.

Короткая формула:

One protocol, one set of mechanisms, thousands of knowledge sources.
Agents decide how to navigate the mesh.

Trip2G можно позиционировать как слой, который превращает разные источники знаний в совместимые agent-readable базы:

Obsidian / Markdown / Telegram / RSS / blogs / docs / Drive / Notion / private notes
        ↓ adapters
Trip2G knowledge bases
        ↓ MCP + instructions + schema + search + provenance
Personal / private / public knowledge mesh
        ↓
Claude / Cursor / Codex / Copilot / custom agents

Это сильнее, чем просто “публикация Obsidian”: появляется протокол и сеть баз знаний, где агент получает не только chunks, но и правила навигации, provenance, права доступа и domain-specific methods.

Как назвать секцию

Варианты для README/docs:

## Knowledge Mesh

## Federated knowledge bases for agents

## One protocol for thousands of knowledge sources

## Build a personal, private or public knowledge mesh

Мой выбор для README:

## Build a knowledge mesh for your agents

Мой выбор для docs/landing:

# Knowledge Mesh Protocol

One protocol, one set of mechanisms, thousands of knowledge sources.

Что это значит продуктово

Trip2G база — это не просто сайт и не просто RAG index.

Это узел сети знаний:

Knowledge Base Node = content + index + schema + instructions + access + MCP tools + update loop

Каждый node может быть:

• public — публичная база, индексируемая и доступная агентам;
• private — командная/проектная база с access control;
• personal — личная память пользователя;
• paid — knowledge product/subgraph;
• mirrored — база, собранная из Telegram/RSS/blogs/docs;
• synthetic — база, которую агент сам поддерживает из внешних источников.

Агент не просто делает vector search. Он читает:

initialize() → как начать с этой базой
instructions() → как себя вести
schema() → какие типы страниц и правила записи
search() → найти релевантные страницы
note_html() → открыть страницу или focused match
custom methods → domain-specific tools

Почему “поверх MCP”

MCP даёт общий транспорт и tool interface.

Trip2G добавляет conventions для knowledge bases:

- AGENTS.md / instructions()
- SCHEMA.md / schema()
- _mcp_initialize.md / initialize()
- index.md как карта базы
- log.md как append-only history
- frontmatter как machine-readable metadata
- wikilinks/backlinks как graph
- source_url/provenance для проверяемости
- access/free/subgraph как права
- webhooks/cron как update loop
- adapters как ingestion layer

То есть Trip2G может сказать:

MCP is the interface. Trip2G is the knowledge-base protocol and operating layer.

README block draft

## Build a knowledge mesh for your agents

Trip2G is not limited to one vault. It gives every knowledge base the same agent-readable interface:

- `search` to discover relevant pages;
- `note_html` to read pages or focused matches;
- `instructions` to learn how to use the base;
- `schema` to understand how knowledge is structured;
- custom `mcp_method` pages for domain-specific tools;
- webhooks and cron to keep the base updated.

Use it to connect public docs, private team notes, personal memory, Telegram channels, RSS feeds, blogs and research archives into one knowledge mesh.

Your agent can decide how to navigate each base: index-first traversal, search/RAG, citations, source verification, or base-specific instructions.

```text
Personal notes ─┐
Team docs ──────┤
Telegram ───────┤
RSS/blogs ──────┤→ Trip2G knowledge bases → MCP → Claude/Cursor/Codex
Public wikis ───┘

One protocol. One set of mechanisms. Thousands of knowledge sources.

## Landing/docs block draft

```markdown
# Knowledge Mesh Protocol

Trip2G turns knowledge sources into MCP-accessible bases that agents can read, cite, update and connect.

Each base carries its own navigation rules:

- where to start;
- which index to read first;
- which sources are authoritative;
- how to cite claims;
- when to use search vs wikilinks;
- whether the agent may update the base;
- which pages expose custom MCP methods.

This lets agents move across many bases without losing context or ownership boundaries.

Public, private, personal meshes

An agent can query public bases across topics and cite stable URLs.

A company agent navigates internal knowledge with access control and provenance.

Your personal agent has one durable memory layer across projects.

Access is scoped by subscription, but the protocol remains the same.

Adapter story

Trip2G should describe adapters as the way to bring sources into the mesh.

Markdown / Obsidian → native sync
Telegram → channel export / sync
RSS/blogs → sitemap/RSS watcher + markdown extraction
Docs → crawler / llms.txt / sitemap
Notion / Drive → future adapters
GitHub → repo/docs/issues/PR ingestion

Anthropic sitemap/RSS → Jina Reader/HTML extraction → raw markdown sources → agent synthesis → Trip2G MCP base

Anthropic official post → wait 1–3 days → collect Telegram discussions / summaries / critiques → add commentary layer → update concepts/timelines

Should Telegram commentary replace independent analysis?

Short answer: no, but it can reduce the work and improve the base.

Do not replace official source analysis with Telegram summaries, because:

• Telegram channels can distort or overfit to hype;
• attribution/provenance is weaker;
• important details may be omitted;
• channels may copy each other;
• public commentary is not canonical.

But Telegram is very useful as a second layer:

official source = canonical facts
Telegram/news commentary = interpretation, framing, objections, community reaction
agent synthesis = durable concept pages and timeline updates

Recommended pipeline:

Day 0:
  Ingest official Anthropic post from sitemap/RSS.
  Save raw markdown.
  Create/update factual summary.

Day 1–3:
  Search Telegram/news/commentary sources.
  Add “What people noticed” section.
  Extract disagreements, examples, implementation notes.
  Link commentary back to the official source.

Day 7:
  Agent consolidates into concept pages and timeline.

This is better than either extreme:

Only official posts → too dry, misses ecosystem reaction.
Only Telegram summaries → noisy, not canonical.
Official + commentary + synthesis → strong Trip2G knowledge base.

How to model commentary pages

Raw official source:

---
type: raw_source
source_kind: official
source_domain: anthropic.com
source_url: https://www.anthropic.com/...
author: Anthropic
published: 2026-...
ingested: 2026-...
---

Telegram commentary source:

---
type: commentary_source
source_kind: telegram
source_channel: example_channel
source_url: https://t.me/...
related_official_source: https://www.anthropic.com/...
published: 2026-...
ingested: 2026-...
confidence: medium
---

Synthesized concept page:

---
type: concept
canonical_sources:
  - https://www.anthropic.com/...
commentary_sources:
  - https://t.me/...
last_reviewed: 2026-...
---

Agent navigation policy for mesh

Each base should expose a retrieval policy:

---
free: true
mcp_method: retrieval_policy
mcp_description: "How agents should navigate this knowledge base and linked bases."
---

Example content:

# Retrieval policy

1. Start with `initialize()`.
2. Read `index.md` for the map of this base.
3. Use `search()` for broad discovery.
4. Use wikilinks for local traversal.
5. Prefer official/canonical sources for factual claims.
6. Use commentary sources for interpretation and objections.
7. When a claim depends on another base, follow its MCP endpoint if available.
8. Cite source URLs and page paths.
9. If updating the base, write to `log.md`.

Mesh registry idea

A future Trip2G mesh can have a registry note:

# Knowledge mesh registry

## Bases

### Anthropic KB

- MCP: `https://anthropic-kb.example.com/_system/mcp`
- Type: public mirrored research/blog base
- Trust: canonical official sources + curated commentary
- Start: `initialize()`
- Best for: Anthropic agents/research/model releases

### Personal notes

- MCP: `https://my-notes.example.com/_system/mcp`
- Type: private personal memory
- Trust: user-owned notes
- Access: private
- Start: `initialize()`

This could be exposed as:

---
free: true
mcp_method: mesh_registry
mcp_description: "Known knowledge bases in this mesh and how agents should use them."
---

Where this fits in README

Recommended README order after current rewrite:

Hero
Quickstart
Connect an AI agent
Build an LLM Wiki
Build a knowledge mesh for your agents  ← new section
Choose your path
Why Trip2G
Core features

Do not put this before quickstart. Mesh/federation is powerful but abstract. It should appear after the user understands one base.

What to say in one sentence

Trip2G makes each knowledge base an MCP node with its own instructions, schema, access rules and update loop — then lets agents navigate many such nodes as a knowledge mesh.

What to avoid

Avoid saying:

Trip2G replaces the web.
Trip2G replaces RAG.
Trip2G automatically understands every source.
Trip2G guarantees truth from Telegram summaries.

Say instead:

Trip2G gives agents a consistent protocol for reading, citing, updating and connecting knowledge bases while preserving source ownership and provenance.

Recommended next task

Add a dedicated section to the README rewrite:

Build a knowledge mesh for your agents

and add a later docs page:

/docs/knowledge-mesh.md

Acceptance:

• explains public/private/personal meshes;
• explains adapters;
• explains agent navigation policy;
• shows official source + Telegram commentary pipeline;
• does not overpromise automatic truth;
• ties back to MCP and LLM Wiki.