Grant Application: CCXT Connector for CoW Protocol/SDK [retro round]

Author: Tantodefi.eth & Bhavya Gor
Date: October 26, 2025
Category: Developer Tooling
Funding Requested: 15,000 xDAI + 15,000 vested COW tokens
Gnosis Chain Address: 0x9B2FB7a8d227cDaA8002f80e8c8A99a19Bb1b969
GitHub: Tantodefi | Bhavya Gor
Contact: tantodefi.eth@proton.me | bhavya.gor9999@gmail.com

About You

We are Tantodefi.eth , experienced developers specializing in blockchain integrations, API development, and trading systems. We've contributed to open-source DeFi projects, including smart contracts, algorithmic trading tools, and developer resources for platforms like BUIDLGuidl's Scaffold-ETH. Our expertise lies in creating accessible tools for DeFi ecosystems, with a focus on standardized APIs for development.

Project Overview

This proposal seeks funding from CoW DAO's retroactive funding round to develop a CCXT library connector for the CoW SDK, enabling seamless integration of CoW Protocol's intent-based trading into the widely used CCXT library. This will allow algorithmic traders to leverage CoW's MEV-protected executions through a unified API, reducing integration barriers and driving protocol adoption. The project builds on prior SDK efforts, such as the community-built Python SDK¹, to enhance developer accessibility and ecosystem growth.

For full details, including feasibility, implementation, and impact metrics, see our Detailed Proposal.

Team

• Tantodefi.eth (Lead Developer): Blockchain engineer with expertise in DeFi integrations and algorithmic trading. Contributed exchange adapters and participated in BUIDLGuidl hackathons. GitHub: tantodefi, X: @tantodefi.
• Bhavya Gor (Co-Developer): Full-stack developer focused on API wrappers and Web3 testing. Built TypeScript/Python SDKs and DeFi tools at BUIDLGuidl. GitHub: bhavyagor12, X: @bhavya_gor.

Project Details

Motivation and Rationale

The CoW Protocol's intent-based architecture, powered by the CoW SDK², offers superior executions with MEV protection and gas efficiency. However, algorithmic traders using CCXT—the standard for 100+ exchanges—face integration hurdles. This connector will map CoW SDK functions (e.g., quoting, order management) to CCXT's API, enabling plug-and-play usage for trading bots and strategies.

Key Benefits:

• Ease of Integration: Add CoW as a CCXT "exchange" with methods like createOrder and fetchOrder.
• Increased Usage: Enable algo traders to route orders to CoW, boosting TVL and solver activity.
• Differentiation: Custom quote comparators highlight CoW's advantages (e.g., 1-5% execution savings) over DEXs like Uniswap.
• Ecosystem Growth: Open-source CCXT contribution³ attracts builders for AI agents and automated trading.

Feasibility

CoW's batch auction model differs from order-book systems, but CCXT supports partial implementations. We assessed:

• Compatibility: Map async quoting/orders via polling, inspired by DEX connectors (e.g., Uniswap).
• Async Handling: SDK-based polling with configurable intervals.
• Rate Limiting: Mirror SDK logic (10-20 quotes/min) to prevent IP blocks.
• Missing Features: Disable order books/tickers; synthesize symbols from metadata.
• Enhancements: Add compareQuoteWithOtherExchanges for multi-venue benchmarking.

This ensures 70-80% CCXT coverage, focusing on trading, similar to prior SDK integrations¹.

Implementation

We will implement a TypeScript-derived CCXT class leveraging the underlying CoW Protocol APIs (via the Order Book API at https://api.cow.fi/), which the CoW TypeScript SDK² is built upon. This allows direct interaction with REST endpoints for maximum functionality while handling rate limiting (e.g., built-in throttling to 10-20 requests/min for /quote) and polling for asynchronous order status updates.

Key API routes for integration:

• Quoting: POST /api/v1/quote – Retrieves a simulated execution price based on intent parameters (e.g., sellToken, buyToken, kind: 'sell'/'buy', amount, userAddress). This maps to CCXT's fetchQuote or pre-order price checks.
• Order Creation: POST /api/v1/orders – Submits a signed intent (order) with parameters like sellToken, buyToken, sellAmount/buyAmount, validTo, appData, kind, partiallyFillable (false for limit orders), and signature. Maps to CCXT's createOrder (limit orders only, as market orders are simulated via quotes).
• Fetch Order: GET /api/v1/orders/{orderUID} – Retrieves order status and details by unique ID. Maps to CCXT's fetchOrder.
• Cancel Order: DELETE /api/v1/orders/{orderUID} – Cancels a pending order. Maps to CCXT's cancelOrder.
• Fetch Trades: GET /api/v1/trades?owner={address}&limit={n} – Retrieves executed trades for a user address. Maps to CCXT's fetchMyTrades.
• Markets/Tokens: GET /api/v1/tokens – Fetches supported tokens to synthesize markets (e.g., token pairs). Maps to CCXT's loadMarkets.

Limitations Assessment: CoW Protocol's intent-based model (users submit preferences as signed messages, delegated to solvers for execution in batch auctions) introduces key differences from traditional exchanges:

• No Real-Time Market Data: Batch auctions (every ~5 minutes) mean no order books, tickers, or OHLCV data. Solvers optimize post-submission using off-chain liquidity, leading to delayed executions and variable final prices.
• Asynchronous Execution: Orders are intents, not immediate; status requires polling (e.g., every 10-30 seconds via fetchOrder) as no websockets exist.
• Order Types: Primarily limit orders; market orders simulated via quotes. No advanced types like stop-loss natively (can be emulated via custom bots).
• Partial Fills: Supported but not default; MEV protection is built-in, reducing front-running risks.
• Dependencies: Requires user wallet for signing intents; balances fetched via RPC, not API.

Optimal Integration into CCXT Adapter:

• Core Focus: Prioritize order lifecycle (quote → create → fetch → cancel → trades) for 70-80% CCXT method coverage.
• Disabled Features: Set has['fetchOrderBook'] = false, has['fetchTicker'] = false, has['fetchOHLCV'] = false, and websocket methods to false in the exchange's features config.
• Custom Extensions: Add fetchQuote for pre-trade simulation and compareQuoteWithOtherExchanges to benchmark against other CCXT venues (normalizing for fees, slippage, gas).
• Polling and Rate Handling: Implement configurable polling for order updates; enforce SDK-like rate limits to avoid IP blocks.
• Extras: Include an example risk management bot using polling to monitor and automate actions (e.g., cancel if not filled within time).

This approach maximizes functionality by abstracting intent delegation, providing seamless algo trading while transparently handling CoW's batch-based limitations.

Milestones

The project spans 8 weeks (October 26 - December 21, 2025):

Milestone	Description	Timeline	Deliverable	Verification
1: Research and Setup	Analyze SDK/CCXT; review DEX connectors; prototype class.	Oct 26 - Nov 2 (Week 1)	Feasibility doc, prototype.	GitHub commit.
2: Core Implementation	Build order lifecycle, polling, rate limiting.	Nov 3 - Nov 16 (Weeks 2-3)	Functional connector, basic tests.	80% test coverage.
3: Advanced Features and Testing	Add comparator/bot; tests/docs.	Nov 17 - Dec 7 (Weeks 4-6)	Beta version, docs.	90%+ test coverage; draft README.
4: Submission and Review	Submit PR to CCXT; iterate.	Dec 8 - Dec 21 (Weeks 7-8)	Merged PR, usage guide.	CCXT merge; metrics report.

Budget

Total: 15,000 xDAI + 15,000 vested COW (12-month vesting).

Category	Amount (xDAI)	Justification
Development	10,000	200 hours @ $50/hr (research, coding).
Testing/Documentation	3,000	60 hours (polling, docs).
Community Engagement	2,000	Feedback, PR reviews, features.
Vested COW Tokens	15,000	Long-term alignment.

Prefer xDAI for liquidity.

Impact and Metrics

• Quantitative: CCXT downloads (npm/GitHub); CoW tx uplift (unique tags); comparator savings (1-5%). Target: 10-20% algo volume growth in 6 months.
• Qualitative: Forum feedback; GitHub stars/forks; developer contributions.
• Verification: Open-source GitHub; on-chain analytics.

This builds on SDK grants¹, expanding CoW's algo trading reach.

Additional Notes

We welcome community feedback to refine this proposal. The project leverages insights from the Python SDK grant¹ for robust integration practices.

CoW DAO Grant Agreement

By submitting this proposal, we agree to adhere to the terms outlined in the CoW DAO Grant Agreement. We commit to transparency, timely delivery of milestones, and open-source contributions to maximize value for the CoW ecosystem.

Full Proposal: HackMD

We look forward to your feedback!

Footnotes

1. Community-built Python SDK Grant ↩ ↩² ↩³ ↩⁴

2. CoW SDK GitHub ↩ ↩²

3. CCXT Contributing ↩