trip2g

Serve a folder of Markdown notes as an MCP server: hybrid search, reading, and sourced answers.

CommunityOnlineNo sign-inGlobalFreeRead-only

What it can do

    What data it sees

    Do you need an account

    No: the server works without sign-in

    Serve a folder of Markdown notes as an MCP server: hybrid search, reading, and sourced answers.

    How to connect

    How to connect trip2g to Claude

    The server address to paste into Claude settings:

    https://trip2g.com/_system/mcp

    1. Open Claude (claude.ai or the desktop app).
    2. Go to Settings → Connectors.
    3. Click Add custom connector.
    4. Paste the server address copied below into Remote MCP server URL and click Add.
    5. In a chat, click + → Connectors and switch the new connector on.

    Custom connectors are available on Free, Pro, Max, Team and Enterprise plans (Free is limited to one). On Team and Enterprise an organization Owner adds the connector first under Organization settings → Connectors.

    Authorization

    After you click Add, a sign-in window for the service opens. Sign in with your own account and approve access. Claude never sees your password.

    How to connect trip2g to ChatGPT

    The server address to paste into ChatGPT settings:

    https://trip2g.com/_system/mcp

    1. Open ChatGPT in a browser (chatgpt.com). A Plus, Pro, Business, Enterprise or Edu plan is required.
    2. Turn on developer mode once: Settings → Apps → Advanced settings → Developer mode.
    3. Open Settings → Connectors and click Create.
    4. Fill in the form: Name (anything), Description (one line about what the service does), MCP server URL (copy it below).
    5. Under Authentication choose OAuth if the service requires sign-in, otherwise None. Click Create.
    6. In a new chat open + → Apps/Connectors and enable the connector.

    OpenAI has renamed this section before (Connectors → Apps/Plugins). If the label differs, search settings for "developer mode". On Business/Enterprise workspaces an admin must allow custom connectors first.

    Authorization

    On first use ChatGPT opens the service's sign-in window. Sign in and approve access.

    How to connect trip2g to Cursor

    The server address to paste into Cursor settings:

    https://trip2g.com/_system/mcp

    Fastest: click Open in Cursor below and confirm the prompt.

    Manually:

    1. In Cursor open Settings → Cursor Settings → MCP and click Add new global MCP server.
    2. Paste the JSON copied below into ~/.cursor/mcp.json (per project: .cursor/mcp.json in the repo root).
    3. Save the file. The server appears in the MCP list; authorize it there if asked.

    Authorization

    If the service needs sign-in, an authorize button appears next to the server in the MCP list.

    Server tool list (11)

    Raw names from tools/list. Only developers need these.

    expandWalk a note's table of contents level by level (progressive disclosure). Canonical call: expand(path=<result.note_path>, toc_path=[...]) — copy path verbatim from a search result's note_path field. Returns the direct children of a TOC node: omit toc_path (or pass []) for the top-level sections, or pass a toc_path to list that section's subsections. Each child has title, level, path, and has_children. A section with subsections lists them; a section without subsections is returned in full (what note_html gives for that toc_path, plus section_html in the payload), so no second call is needed to read a leaf. This cannot be turned off, and a client that wants only structure never triggers it: has_children on each listed child says where descending would turn into reading.
    federated_expandWalk a remote note's table of contents level by level inside a connected knowledge base (progressive disclosure), same as expand. Canonical call: federated_expand(kb_id=..., path=<result.note_path>, toc_path=[...]). Omit toc_path for the top level, or pass a toc_path to list that node's subsections. A section with subsections lists them; a section without subsections is returned in full, as federated_note_html would return it — has_children on each listed child says where that happens.
    federated_instructionsFetch the instructions/guidance for a federated knowledge base by kb_id (e.g. "philosophers/nietzsche") — read a base's own conventions before searching it. Nested bases are addressed with '/' and the call routes through each peer recursively.
    federated_note_htmlRead a remote note inside a connected knowledge base. Canonical call, copying fields verbatim from a federated_search result: federated_search(kb_id="philosophers/<author>", query) -> federated_note_html(kb_id="philosophers/<author>", path=<result.note_path>) — the standard way to descend into a leaf corpus and read real content there, not hub cards. federated_note_html(kb_id=..., match_id=<match.match_id>) reads just the focused chunk around a hit. Only pass pid/note_id if you already copied that exact id from a result. path is a string like "concepts/x.md"; match_id is "p<pid>:c<chunk>"; a value like ":" or "/hub/goethe.md" is a PATH, not a note_id.
    federated_searchSearch connected knowledge bases. Returns snippets with heading breadcrumbs (title > section > subsection) and a precise toc_path per match, same as search; results also carry an absolute kb_id (string) to use verbatim on follow-up calls. Pass kb_id for one base, kb_ids for selected bases, or omit both to fan out. Nested bases are addressed with '/': kb_id "philosophers/nietzsche" routes through the 'philosophers' peer to the base it federates (recursive), up to 3 levels deep. Canonical call: federated_search(kb_id="philosophers/<author>", query) -> federated_note_html(kb_id="philosophers/<author>", path=<result.note_path>) — the standard way to descend into a leaf corpus and read real content, not hub cards.
    federated_similarFind remote notes similar to a known note reference inside a connected knowledge base. Preferred: path (a federated_search result's note_path field).
    instructionsFull tool reference for the trip2g documentation base
    note_htmlRead a note. Canonical calls, copying fields verbatim from a search result: search(query) -> note_html(path=<result.note_path>) reads the whole note; search(query) -> note_html(match_id=<match.match_id>) reads just the focused chunk around a hit (cheaper, targeted); expand(path=<result.note_path>, toc_path=[...]) -> note_html(path=<result.note_path>, toc_path=[...]) reads one exact section. Only pass pid/note_id if you already copied that exact integer from a result's note_id field — never invent one. path is a string like "concepts/x.md"; match_id is "p<pid>:c<chunk>"; a value like ":" or "/hub/goethe.md" is a PATH, not a note_id.
    searchSearch notes by query. Returns snippets with a heading breadcrumb (title > section > subsection) that locates the approximate section, plus a precise toc_path per match. Each result carries note_path (string) and note_id (integer); each match carries match_id (string, form "p<pid>:c<chunk>"). Drill-down workflow: 1) search to find the approximate section via the breadcrumb; 2) call note_html(path=<result.note_path>, toc_path=[...]) to read the matched section, or expand(path=<result.note_path>, toc_path=[...]) to navigate the note's structure level by level; 3) note_html(path=<result.note_path>, match_id=<match.match_id>) for a focused chunk window. Each match also carries section_url — a link straight to that heading, for citing the section rather than the whole note.
    similarFind related notes from a known note reference. Preferred: path (a search result's note_path field). Use this after opening a promising note when you need nearby context.
    wikiWiki Knowledge Base Instructions