Generate discoverable code from MCP servers for agent tool usage
Wellknown found it in public sources; nobody has proven control of it yet. Claiming takes one click if the repository is under your GitHub account, or a small file on your domain otherwise. Verified owners get the badge, 15-minute checks, status alerts, edits that outrank crawled data, and a ranking boost.
Agents can do it too: POST https://wellknown.network/api/v1/claims with {"agent":"mcp-coded-tools","method":"well_known_file"} — machine-readable steps at claim.json, guide at /docs/claim.
Everything here was measured by our prober or read from a registry. Nothing is self-reported.
Attributed to the source that supplied each field. Treated as claims, not facts.
# mcp-coded-tools [](https://badge.fury.io/py/mcp-coded-tools) [](https://pypi.org/project/mcp-coded-tools/) [](https://opensource.org/licenses/MIT) [](https://github.com/bluman1/mcp-coded-tools/actions) Generate discoverable code from MCP servers for AI agent tool usage. ## Why? The [Model Context Protocol (MCP)](https://modelcontextprotocol.io/) lets AI agents connect to external tools and data. However, as Anthropic's [engineering post](https://www.anthropic.com/engineering/code-execution-with-mcp) explains, loading hundreds or thousands of tool definitions directly into an agent's context window is inefficient: - Tool definitions consume excessive tokens (100K+ tokens for large tool sets) - Intermediate results flow through the context window repeatedly - Agents become slower and more expensive at scale **The solution**: Present MCP servers as *code APIs* that agents can discover and use through a filesystem interface. This approach reduces token usage by up to 98.7% while enabling more powerful agent workflows. **The problem**: Manually writing wrapper code for each MCP tool is tedious. **mcp-coded-tools**: Automatically generate discoverable Python code from any MCP server. ## Installation ```bash pip install mcp-coded-tools ``` ## Quick Start ### CLI Usage ```bash # Generate code from popular MCP servers mcp-coded-tools generate \ --command "npx -y @modelcontextprotocol/server-github" \ --output ./servers \ --server-name github # Generate from multiple servers for complete workflows mcp-coded-tools generate \ --command "npx -y @modelcontextprotocol/server-github" \ --command "npx -y @modelcontextprotocol/server-postgres" \ --command "python slack_mcp_server.p…
Mapped onto the structured taxonomy from declared text and observed tool names. Confidence shown for derived entries.
Every source is kept verbatim. Field changes are logged as events.