{"id":29989730,"url":"https://github.com/ark2016/mcp-study","last_synced_at":"2025-09-16T15:33:41.934Z","repository":{"id":305003829,"uuid":"1021574427","full_name":"ark2016/MCP-study","owner":"ark2016","description":null,"archived":false,"fork":false,"pushed_at":"2025-07-17T16:51:37.000Z","size":34,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"main","last_synced_at":"2025-08-05T00:12:41.040Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/ark2016.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2025-07-17T15:51:35.000Z","updated_at":"2025-07-17T16:51:40.000Z","dependencies_parsed_at":"2025-07-17T22:26:57.829Z","dependency_job_id":null,"html_url":"https://github.com/ark2016/MCP-study","commit_stats":null,"previous_names":["ark2016/mcp-study"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/ark2016/MCP-study","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ark2016%2FMCP-study","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ark2016%2FMCP-study/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ark2016%2FMCP-study/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ark2016%2FMCP-study/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/ark2016","download_url":"https://codeload.github.com/ark2016/MCP-study/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ark2016%2FMCP-study/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":275440355,"owners_count":25465109,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","status":"online","status_checked_at":"2025-09-16T02:00:10.229Z","response_time":65,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2025-08-04T23:24:22.200Z","updated_at":"2025-09-16T15:33:41.926Z","avatar_url":"https://github.com/ark2016.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# MCP Chat\n\nMCP Chat is a command-line interface application that enables interactive chat capabilities with AI models through the Anthropic API. The application supports document retrieval, command-based prompts, and extensible tool integrations via the MCP (Model Control Protocol) architecture.\n\n## Prerequisites\n\n- Python 3.9+\n- Anthropic API Key\n\n## Setup\n\n### Step 1: Configure the environment variables\n\n1. Create or edit the `.env` file in the project root and verify that the following variables are set correctly:\n\n```\nANTHROPIC_API_KEY=\"\"  # Enter your Anthropic API secret key\n```\n\n### Step 2: Install dependencies\n\n#### Option 1: Setup with uv (Recommended)\n\n[uv](https://github.com/astral-sh/uv) is a fast Python package installer and resolver.\n\n1. Install uv, if not already installed:\n\n```bash\npip install uv\n```\n\n2. Create and activate a virtual environment:\n\n```bash\nuv venv\nsource .venv/bin/activate  # On Windows: .venv\\Scripts\\activate\n```\n\n3. Install dependencies:\n\n```bash\nuv pip install -e .\n```\n\n4. Run the project\n\n```bash\nuv run main.py\n```\n\n#### Option 2: Setup without uv\n\n1. Create and activate a virtual environment:\n\n```bash\npython -m venv .venv\nsource .venv/bin/activate  # On Windows: .venv\\Scripts\\activate\n```\n\n2. Install dependencies:\n\n```bash\npip install anthropic python-dotenv prompt-toolkit \"mcp[cli]==1.8.0\"\n```\n\n3. Run the project\n\n```bash\npython main.py\n```\n\n## Usage\n\n### Basic Interaction\n\nSimply type your message and press Enter to chat with the model.\n\n### Document Retrieval\n\nUse the @ symbol followed by a document ID to include document content in your query:\n\n```\n\u003e Tell me about @deposition.md\n```\n\n### Commands\n\nUse the / prefix to execute commands defined in the MCP server:\n\n```\n\u003e /summarize deposition.md\n```\n\nCommands will auto-complete when you press Tab.\n\n## Development\n\n### Adding New Documents\n\nEdit the `mcp_server.py` file to add new documents to the `docs` dictionary.\n\n### Implementing MCP Features\n\nTo fully implement the MCP features:\n\n1. Complete the TODOs in `mcp_server.py`\n2. Implement the missing functionality in `mcp_client.py`\n\n### Linting and Typing Check\n\nThere are no lint or type checks implemented.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fark2016%2Fmcp-study","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fark2016%2Fmcp-study","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fark2016%2Fmcp-study/lists"}