How real projects summarise themselves for language models.
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
DavidHDevllms.txtDavidHDev/canvas-ui/public/llms.txt
WebGL and WebGPU (vgpu) builds, browser support, and how the WebGPU build works - [MCP Server](https://canvasui.dev/docs/mcp): Use the registry with the shadcn MCP server so AI assistants
No other project uses it yet
NewFuturellms.txtNewFuture/DDNS/docs/llms.txt
ddns.newfuture.cc/release.md)) ### Configuration Guides - CLI Arguments: https://ddns.newfuture.cc/config/cli ([.md](https://ddns.newfuture.cc/config/cli.md)) - MCP Server: https://ddns.newfuture.cc/config/mcp ([.md](https://ddns.newfuture.cc/config/mcp.md)) - Environment Variables: https://ddns.newfuture.cc/config/env ([.md](https://ddns.newfuture.cc
No other project uses it yet
dagu-orgReads credentialsllms.txtdagu-org/dagu/llms.txt
Python or PowerShell script. Inspect a workbook first with `dagu xlsx inspect` or the MCP `workbook` read target. - Prefer `git.worktree.add` and `git.worktree.remove` when steps need isolated branches inside an existing
dagucloudReads credentialsllms.txtdagucloud/dagu/llms.txt
Python or PowerShell script. Inspect a workbook first with `dagu xlsx inspect` or the MCP `workbook` read target. - Prefer `git.worktree.add` and `git.worktree.remove` when steps need isolated branches inside an existing
openagents-orgReads credentialsllms.txtopenagents-org/openagents/llms.txt
MyNetwork mode: centralized transports: - type: http config: port: 8700 serve_mcp: true # Expose as MCP server - type: grpc config: port: 8600 mods: - name: openagents.mods.workspace.messaging enabled: true config: default_channels: - name
No other project uses it yet
txn2llms.txttxn2/kubefwd/docs/llms-full.txt
kubefwd.internal/api` ## Key Endpoints ### Health & Info - `GET /api/health` - Health check - `GET /api/info` - Server information ### Services - `GET /api/v1/services` - List forwarded services - `GET /api/v1/services/:key` - Get specific service - `POST /api/v1/services` - Add service
No other project uses it yet
flypythoncomllms.txtflypythoncom/python/llms.txt
stateless 2026-07-28 MCP tool server in pure Python — reuses the reviewed mcp-server example core (EN+ZH). - `courses/da-eda/`: Exploratory data analysis with pandas over a messy shop export
No other project uses it yet
steveseguinllms.txtsteveseguin/vdo.ninja/llms.txt
self-hosting project. Read its limitations; the wrapper is not itself an SFU/media distribution server. - [Broadcast-box with VDO.Ninja support](https://github.com/steveseguin/broadcast-box-with-vdon-support): Experimental fork demonstrating a self-hosted Meshcast-like
No other project uses it yet
langroidReads credentialsllms.txtlangroid/langroid/llms.txt
changes to how `FastMCPServer` forwards image context and resources, and added optional persistence for MCP server connections. The handler parameter analysis improvements were made to support more robust type checking
Steady14 mentions in 2 weeks
No other project uses it yet
datamodel-code-generatorllms.txtdatamodel-code-generator/datamodel-code-generator/docs/llms-full.txt
models from JSON Schema](https://github.com/topoteretes/cognee/blob/main/cognee/shared/graph_model_utils.py)* - [e2b-dev/E2B](https://github.com/e2b-dev/E2B) - *[Generate MCP server TypedDict models via Makefile](https://github.com/e2b-dev/E2B/blob/main/packages/python-sdk/Makefile)* - [DataDog/integrations-core](https://github.com/DataDog/integrations-core) - *[Config models
datamodel-code-generatorllms.txtdatamodel-code-generator/datamodel-code-generator/docs/llms.txt
from MCP Tool Schemas](https://datamodel-code-generator.koxudaxi.dev/mcp-tools/): Generate Python models from Model Context Protocol (MCP) tool schema profiles. - [Generate from JSON / YAML / CSV Data](https://datamodel-code-generator.koxudaxi.dev/jsondata/): Generate Pydantic models
koxudaxillms.txtkoxudaxi/datamodel-code-generator/docs/llms-full.txt
models from JSON Schema](https://github.com/topoteretes/cognee/blob/main/cognee/shared/graph_model_utils.py)* - [e2b-dev/E2B](https://github.com/e2b-dev/E2B) - *[Generate MCP server TypedDict models via Makefile](https://github.com/e2b-dev/E2B/blob/main/packages/python-sdk/Makefile)* - [DataDog/integrations-core](https://github.com/DataDog/integrations-core) - *[Config models
cosmicstack-labsPipes a download into a shellllms.txtcosmicstack-labs/mercury-agent/docs/llms-full.txt
# Running an agent overnight: what breaks first > We read Mercury's scheduler and budget
ascending-llcReads credentialsllms.txtascending-llc/jarvis-registry/docs/llms-full.txt
Jarvis Registry is a self-hostable enterprise gateway and registry for governed access to MCP servers, A2A agents, and private AI skills. Last updated
ascending-llcllms.txtascending-llc/jarvis-registry/docs/llms.txt
Jarvis Registry is a self-hostable enterprise gateway and registry for governed access to MCP servers, A2A agents, and private AI skills. Last updated
erigontechReads credentialsllms.txterigontech/erigon/llms-full.txt
binary execution + consensus, no extra software 40+ AI query tools via built-in MCP server ## Key Architectural & Performance Advantages Erigon's architecture provides measurable improvements in cost, performance, and reliability
erigontechllms.txterigontech/erigon/llms.txt
Authentication](https://docs.erigon.tech/fundamentals/tls-authentication): Mutual TLS setup for securing gRPC and RPC daemon endpoints. - [MCP Server](https://docs.erigon.tech/fundamentals/mcp): Model Context Protocol server for AI-assisted node interaction and queries
Ataraxy-LabsPipes a download into a shellllms.txtAtaraxy-Labs/sem/docs/llms.txt
those buckets. ## Architecture Cargo workspace: sem-core (library), sem-cli (binary) and sem-mcp (MCP server). - tree-sitter for code parsing (native Rust, not WASM) - git2 for in-process
Steady11 mentions in 2 weeks
No other project uses it yet
Microsoftllms.txtmicrosoft/skills/docs/llms-full.txt
Azure text translation](https://learn.microsoft.com/en-us/azure/ai-foundry/azure/ai-services/translator/text-translation/overview?context=/azure/foundry/context/context?view=foundry) - [Azure document translation](https://learn.microsoft.com/en-us/azure/ai-foundry/azure/ai-services/translator/document-translation/overview?context=/azure/foundry/context/context?view=foundry) - [Connect to MCP server](https://learn.microsoft.com/en-us/azure/ai-foundry/agents/how-to/tools/model-context-protocol?view=foundry) - [MCP authentication](https://learn.microsoft.com/en-us/azure/ai-foundry/agents/how-to/mcp-authentication?view=foundry) - [Build your own MCP server
2 projects use a version of this
Microsoftllms.txtmicrosoft/skills/docs/llms.txt
Azure text translation](https://learn.microsoft.com/en-us/azure/ai-foundry/azure/ai-services/translator/text-translation/overview?context=/azure/foundry/context/context?view=foundry) - [Azure document translation](https://learn.microsoft.com/en-us/azure/ai-foundry/azure/ai-services/translator/document-translation/overview?context=/azure/foundry/context/context?view=foundry) - [Connect to MCP server](https://learn.microsoft.com/en-us/azure/ai-foundry/agents/how-to/tools/model-context-protocol?view=foundry) - [MCP authentication](https://learn.microsoft.com/en-us/azure/ai-foundry/agents/how-to/mcp-authentication?view=foundry) - [Build your own MCP server
2 projects use a version of this
A markdown file at a website's root that gives language models a short guide to the site and links to the pages worth reading.
The same idea with the content included, so an agent can read the documentation in one request.
Agents and tools that fetch documentation on someone's behalf. It's a proposal, not a standard, and support varies.
Start with a one-line summary, then sections of links with a sentence each. The examples here show what real projects do.
