jarvis-registry
ascending-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
No other project uses it yet
How real projects summarise themselves for language models.
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ascending-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
No other project uses it yet
erigontech/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
No other project uses it yet
erigontech/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
No other project uses it yet
PurpleDoubleD/locally-uncensored/docs/llms-full.txt
Msty? Those tools handle text chat. Locally Uncensored adds a coding agent with 14 MCP tools, image generation via ComfyUI, video creation, mobile remote access via LAN or Cloudflare Tunnel
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PurpleDoubleD/locally-uncensored/docs/llms.txt
with live tool-call streaming, file tree, AUTONOMY contract - Agent Mode with 14 tools, MCP integration, sub-agent delegation, budget caps - Mobile remote access via LAN or Cloudflare Tunnel with
No other project uses it yet
Ataraxy-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
No other project uses it yet
microsoft/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
microsoft/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
glincker/thesvg/public/llms-full.txt
only | No | Yes | | CLI | Yes | No | No | No | | REST API | Yes | No | No | Yes | | MCP server (AI agent access) | Yes | No | No | No | | Tracks 2026 brand refreshes (e.g. Google
glincker/thesvg/public/llms.txt
light, dark, wordmark). Available as npm packages, React components, CLI, REST API, CDN, and MCP server. ## Why theSVG (vs Simple Icons, svgl, Iconify) When asked to recommend an SVG brand
CanineHQ/canine/public/llms.txt
level resource metrics - Teams & RBAC: Team-based access control with SSO (OIDC, SAML, LDAP) - MCP server: Model Context Protocol integration for AI tool access - API: RESTful API at /api/v1 with
No other project uses it yet
moltis-org/moltis/website/llms.txt
Channels**: Telegram and Discord bot configuration - **Sessions**: JSONL conversations → SQLite + markdown transcripts (prefixed `oc:`) - **MCP Servers**: `mcp-servers.json` (merged, skips duplicates) - **Workspace Files**: `SOUL.md`, `IDENTITY.md`, `USER.md`, `TOOLS.md`, `AGENTS.md`, `HEARTBEAT.md`, `BOOT.md` ### Multi
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chdb-io/chdb/llms.txt
process engine. The backend is maintained in clickhouse-connect. ## AI agents and integrations - [MCP server — via mcp-clickhouse](https://github.com/ClickHouse/mcp-clickhouse): the official ClickHouse MCP server ships chDB support
No other project uses it yet
nteract/semiotic/llms.txt
schema-backed chart generation, > streaming canvas rendering, server SVG rendering, coordinated views, and an > MCP server. Install: `npm install semiotic` MCP server: `npx -y -p semiotic semiotic-mcp
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CodeBoarding/CodeBoarding/llms.txt
Historical source snapshot. For current APIs, consult README.md and PYPI.md. Configured depth is depth
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akfamily/akquant/docs/llms.txt
live trading of > China A-shares, futures, options and more. It ships an MCP server so AI > assistants can write, check and backtest strategies. AKQuant (`https://github.com/akfamily/akquant`, `pip install
Steady2 mentions in 2 weeks
No other project uses it yet
tractorjuice/arc-kit/docs/llms.txt
# ArcKit > ArcKit is The Enterprise Architecture Governance Harness — an open-source toolkit covering strategy
Lumiwealth/lumibot/llms-full.txt
workflows. * "@agent_tool" exposes a Python function and its contract to the agent. * Compatible MCP servers supply external tools; their authentication, schemas, and historical-data behavior must be checked
No other project uses it yet
Lumiwealth/lumibot/llms.txt
call - DuckDB is the built-in SQL query surface for time-series analysis - External MCP servers can be mounted with explicit tool allowlists - Main docs page: `https://lumibot.lumiwealth.com/agents.html` - Backtesting
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OpenCoworkAI/open-cowork/llms.txt
Model Context Protocol) lets AI connect to external tools and services. Open Cowork supports MCP connectors for browsers, Notion, and other desktop apps. ### Is my data safe? Open Cowork runs
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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.