mcpField
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Contexter

Contexter

Remote
contexterai.comMemory & Knowledge1Updated 9w ago

About Contexter

Contexter is a hosted remote MCP server for people who want to keep project context available across AI assistants and Telegram. It stores only explicitly saved records and lets people share contexts across tools and with collaborators.

Key features

  1. 01Shared project contexts across assistants
  2. 02Explicitly save records and files
  3. 03Read and update context records
  4. 04Share contexts with people and Telegram
  5. 05Confirm sharing and deletion actions

Use cases

  1. 01Continue a project between ChatGPT and Claude
  2. 02Share project context with a collaborator
  3. 03Keep opted-in Telegram group decisions

MCP support

Contexter provides a hosted MCP server at `https://contexterai.com/mcp`, using Streamable HTTP and OAuth 2.1. MCP clients can read, save, update, share, and remove context data through its tools.

Configuration

Remote servers need no local install. Pick your client, then copy the config or install in one click.

Endpointhttps://contexterai.com/mcp
Copy install command
Claude CodeTerminal
Cursor.cursor/mcp.json
VS Code.vscode/mcp.json
Claude Desktopclaude_desktop_config.json
Windsurf~/.codeium/windsurf/mcp_config.json

Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.

Tools

Details

From the project README

Contexter

Share one AI context across ChatGPT, Claude and Telegram.

Save what you worked out with one AI, continue it in another — and share the context with people in Telegram, who keep working on it in their own AI.

Contexter is a hosted remote MCP server. This repository is its public documentation: the connection details, the tool catalogue and what does and does not move between tools. The server itself is hosted and closed-source — there is nothing to install and no key to manage.

  • Homepage: https://contexterai.com
  • MCP endpoint: https://contexterai.com/mcp
  • Transport: Streamable HTTP
  • Authentication: OAuth 2.1 (with protected-resource metadata discovery)
  • Telegram bot: @ai_contexter_bot
  • Status: early access, free, open to everyone

The problem it solves

You plan something in ChatGPT. You continue it in Claude. You discuss it in a Telegram group. Every hop, you re-explain the project — and the person you are working with cannot pick it up at all, because your history lives inside your account.

Contexter gives the project one context instead of one copy per tool. Both assistants read and write the same records. You can share that context with a person, and they continue it in whichever AI they use.

Nothing is imported automatically. Connecting an assistant does not hand Contexter your chat history. Only the records you explicitly save — or ask your assistant to save — end up in a context.


Connecting

Claude

Add a custom connector pointing at https://contexterai.com/mcp. Claude discovers the OAuth endpoints on its own; you sign in through Telegram and approve access once.

ChatGPT

Add Contexter as a connector with the same URL. Same OAuth flow.

Any other MCP client

Anything that speaks Streamable HTTP with OAuth 2.1 works the same way — point it at https://contexterai.com/mcp.

Full walkthroughs, including what travels between each pair of tools:


What you can ask an assistant to do

Once connected, you talk to your assistant normally. For example:

Create a context called "Kitchen renovation" in Contexter and put my measurement notes in it.

What is in my Dolomites hike context?

Save this comparison to the AI-bot context and share it with Anna.


Tool catalogue

Twenty-six tools in four groups. Write tools require a human decision — the client acts for a person, and irreversible steps (sharing, publishing to a room, deletion) are confirmed rather than assumed.

Reading (8) — list_contexts, get_context_card, get_context_feed, list_records, list_sources, get_artifact, get_file, read_image_content

Saving (7) — save_artifact, save_file, create_context, add_records_to_context, update_artifact, update_context, set_context_notifications

Sharing (5) — share_context, revoke_context_access, check_share_audience, deliver_to_chat, invite_room_to_context

Removing (6) — remove_record_from_context, delete_record, leave_context, restore_record, delete_context, restore_context

Scopes, response shapes and the reasoning behind each one: contexterai.com/developers.


Use cases

Two assistants, one project. Research in ChatGPT, drafting in Claude. The plan lives in a context both reach, so neither one starts from an empty page.

Two people, two different AIs. You share the context, not a document export. The other person opens it from whatever assistant they already pay for.

A group chat that does not lose its decisions. Add the bot to a Telegram group. Messages from the people who opt in become records; the context built from the chat is shared with those same people, and each of them works on it in their own AI, outside the group.


Privacy

  • AI chat history is never imported. Saving is always explicit.
  • A record's visibility is the visibility of the context it is in. There are no hidden audiences: every shared context shows exactly who can see it.
  • In a Telegram group, only the messages of people who joined in are collected. Anyone who has not is not collected at all.
  • Deletion is reversible for 7 days.

Privacy policy · Security model in plain words · Terms · Subprocessors


Support

Open an issue here, or message @ai_contexter_bot in Telegram. Questions and answers for people already using it: contexterai.com/help.

Comments

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New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.