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Claude Chat

Connects MCP clients to Anthropic Claude for text chat, vision, live web search, extended thinking, and model discovery.

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Overview

The claude-chat MCP server connects MCP clients to Anthropic's Claude Messages API through a Rust application using stdio and JSON-RPC 2.0. It provides tools for text conversations, image analysis from URLs, live web search with cited sources, extended thinking, and model listing. Configure an Anthropic API key and optional defaults, then register the compiled binary with an MCP client. Reach for it when an agent needs Claude-specific capabilities through an MCP tool interface.

Use cases

  • Send multi-turn Claude conversations from an MCP client
  • Analyze remotely hosted images with Claude vision
  • Retrieve current information through Claude web search
  • Compare available Claude model IDs before selecting one
  • Enable extended thinking for supported chat requests

Key features

  • Anthropic Messages API access over MCP
  • Multi-turn chat with system prompts
  • Image analysis from HTTP or HTTPS URLs
  • Live web search with cited sources
  • Extended thinking with configurable budgets
  • Cached Claude model listing

Tools13

What Claude Chat lets your agent do. Expand a tool for its parameters.

Self-reported~287 tokens of context

Security & health

What it can reach and how reliably it runs — from our own checks, not the maintainer’s claims.

ActiveLast checked 2d ago

Recent health check succeeded.

4/4 checks healthy over the last 30d

Adoption & maintenance

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Last commit1mo agoMost recent push to the default branch.
Tools exposed13Callable tools this server registers over MCP.
Directory activity3 viewsConfig copies, upvotes, and views on AllMCPs.

How Claude Chat works

What claude-chat MCP server does

The claude-chat MCP server exposes Anthropic's Messages API as MCP tools for clients that communicate over stdio. It supports ordinary Claude conversations, image analysis, live web search, and model discovery. The implementation is written in Rust and sends requests to Anthropic using an API key funded with API credits.

The chat tool accepts a required prompt and can receive prior user and assistant messages as a JSON array. Optional parameters set a system prompt, model, temperature, output limit, and extended-thinking budget. When thinking is enabled, the response includes reasoning in a [thinking] block, and the server raises the output limit above the requested thinking budget.

How it works

MCP clients start the compiled claude-chat executable and communicate with it through standard input and output. The process uses JSON-RPC 2.0 to expose four tools: chat, chat_with_vision, chat_with_search, and list_models.

Vision requests require both a text prompt and an HTTP or HTTPS image URL. Search requests let Claude perform live web searches on the server side and return answers with cited sources. The search tool accepts max_uses, which defaults to five searches for a request. Model results from list_models are cached for five minutes.

Setup and configuration

The claude-chat MCP server requires Rust with edition 2024 support and an Anthropic API key from the Anthropic Console. Create ~/.config/mcp-server-claude-chat/config.toml from the provided example, then set the required api_key value. Startup fails if the configuration file is absent or the key is empty.

Optional TOML settings include base_url, default_model, and default_max_tokens. base_url can point to an Anthropic-compatible gateway instead of the default Anthropic endpoint. Build the release executable with cargo build --release, then register its path in an MCP client's server configuration. Claude Desktop and Claude Code examples are provided in the project documentation.

Tools and capabilities

  • chat supports single-turn and multi-turn text requests, system prompts, model selection, temperature, maximum output tokens, and extended thinking.
  • chat_with_vision sends a prompt and remote image URL to a vision-capable Claude model.
  • chat_with_search enables Claude's live web search and returns cited results.
  • list_models reports available Claude model IDs without parameters.

Limitations and notes

The claude-chat MCP server requires Anthropic API credits; Claude Pro or Max subscriptions are not supported for this third-party server. Web search must be enabled by an organization administrator in the Claude Console, and Anthropic charges an additional $10 per 1,000 searches on top of token costs.

Conversation history for chat must contain only user and assistant roles. Put system instructions in system_prompt instead. The vision tool accepts image URLs only, not local file paths. Anthropic does not provide an embeddings endpoint in this server, so there is no embedding tool.

The project is licensed under MIT.

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Frequently Asked Questions about Claude Chat

claude-chat is an MCP server that connects MCP clients to Anthropic's Claude Messages API through a Rust stdio process. Its main tools send text chats, analyze images from URLs, run live web searches with citations, and list available Claude models. It uses Anthropic API credits rather than Claude subscriptions.

Build it with Rust using `cargo build --release`, configure an Anthropic API key in `~/.config/mcp-server-claude-chat/config.toml`, and register the resulting executable with your MCP client. The project includes configuration examples for Claude Desktop and Claude Code.

No, claude-chat requires an Anthropic API key and API credits. Claude Pro and Max subscriptions are not supported for this third-party server. An Anthropic-compatible gateway can be used by setting the optional `base_url` configuration value.

The `chat_with_search` tool lets Claude search the web on the server side and return an answer with cited sources. You can set `max_uses`, which defaults to five searches per request. Web search must be enabled by an organization administrator and incurs an additional Anthropic charge.

No, the vision tool requires an image URL using `http://` or `https://`. Provide that URL together with a text prompt to `chat_with_vision`; local file paths are not supported by the documented interface.

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