Funding Proposal by VertexPoint Labs: Canton Network MCP + Skills

CLOSEDPull Request
by sunstrike22812-05-2026Declined
50K CC requested
daml-toolingchampion-confirmed
References:CIP-0100
View on GitHub ↗← All Proposals

Development Fund Proposal Submission

Proposal file: Link to the proposal added in this PR: /proposals/mcp-and-skills-by-vertexpoint.md

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Summary

This proposal introduces Canton MCP and Canton LLM Skills, two complementary open-source packages (Apache 2.0) that turn any modern LLM into a Canton-fluent developer assistant. The Canton MCP server exposes 21 deterministic tools across four layers (docs/search, lint/validate, scaffold/generate, live data access) so any AI assistant or autonomous agent can build, validate, and operate Canton applications from a single prompt. The Canton LLM Skills bundle ships the same canonical knowledge in 6 platform formats for clients without MCP support, including consumer ChatGPT, GitHub Copilot, OpenCode, and on-premise Llama / Mistral / Qwen deployments at financial institutions. Together they make Canton developer onboarding "one prompt, one install command, a working Canton project ready to ship", and make live Canton data (Featured App metrics, traffic burnt, reward markers per $1 burnt, transaction history, mining rounds, AmuletRules, balances) accessible to any LLM or agentic system without per-project API integration.

It works with any LLM today and after the next model release: no GPU budget, no fine-tuning, no ML team. M3 includes a NODERS-style adoption-tied bonus (50,000 CC per verified independent adopter, capped at 3) to align proposer incentives with ecosystem outcomes. VertexPoint Labs (TrustedPoint) commits to long-term open-source maintenance with concrete per-Canton-release and per-Splice-release SLAs, plus continuation grant intent per CIP-0100 at month 3.

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Checklist

  • [x] Proposal file added under /proposals/
  • [x] Milestones and funding amounts defined
  • [x] Acceptance criteria included
  • [x] Alignment with Canton priorities described

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Notes for Reviewers

This proposal fills two concrete gaps that are blocking AI-driven adoption of Canton today:

1. LLMs hallucinate Canton APIs. ~85% of developers (Stack Overflow Developer Survey 2025) rely on LLM assistants. Without MCP and Skills support, those assistants regularly emit deprecated endpoints, mis-formatted JSON Ledger API v2 bodies, missing disclosedContracts, and broken DAML syntax. Each Canton dApp team rewrites the same workarounds.

2. LLMs cannot access Canton data. There is no standardised way for an LLM or AI agent to query Featured App metrics, mining rounds, AmuletRules, or transaction state. Canton is effectively invisible to the AI tooling that 85% of developers and a growing share of agentic systems already use.

The proposal delivers open-source, reusable infrastructure under Apache 2.0 (no "open core", no vendor lock-in), covering two Dev-Fund template categories: daml-tooling (DAML compilation, scaffolding, gotchas) and canton-apis (JSON Ledger API v2 body shapes, JWT claims, disclosed-contract handling, Scan API integration). Tech & Ops Committee can pick a primary label.

Reference precedents: NODERS Funding Proposal #38 (adoption-tied per-Featured-App payment), DA dApp SDK #69, Peaceful Studio C# / .NET SDK #46.

Relevant work / Channels

  • TrustedPoint website - https://trusted-point.com
  • GitHub - https://github.com/trusted-point
  • X - https://twitter.com/Trusted_Point
  • Telegram - https://t.me/TrustedPointCorp