lendwise

lendwise

MCP server for LendWise to compare DeFi supply markets across Aave V3, Morpho, and Compound V3 on 8 chains. It helps find best markets and optimize allocations based on real yield data.

Category
Visit Server

README

@lendwise/mcp

Unified view for lending markets. One standard.

MCP server for Lendwise — compare and optimize DeFi supply/borrow markets across Aave V3, Morpho and Compound V3 over live yield data.

It answers questions like "I have $1,000 to place in DeFi for the next 6 months — what are the best markets?" against real yield data, in about four tool calls.

Read-only. It compares markets; it never signs a transaction.

Install

Hosted (Streamable HTTP)

Point any MCP client at https://mcp.lendwise.fi/mcp — nothing to install. With Claude Code:

claude mcp add --transport http lendwise https://mcp.lendwise.fi/mcp

Local (stdio)

// claude_desktop_config.json / .mcp.json
{
  "mcpServers": {
    "lendwise": {
      "command": "npx",
      "args": ["-y", "@lendwise/mcp"]
    }
  }
}

No API key. The server holds no secrets — it speaks only HTTPS to the public Lendwise API.

Tools

tool what it's for
list_market_universe Every asset, chain and protocol that actually exists, with counts. Call this first — it's what stops an agent guessing a filter value that isn't there.
find_best_markets Current supply markets ranked by net APY. Filtering and sorting happen server-side. Defaults to ≥ $1M TVL.
get_market_details One market in full: protocol metadata, collaterals, APY split into base / rewards / fees.
get_market_history Daily net-APY series plus mean / stddev / min / max — the stability signal a long horizon needs.
optimize_allocation Split an amount across markets at a target diversification. Returns per-market amounts, blended APY, projected 6-month yield.

Why the TVL floor exists

find_best_markets defaults to minTvlUsd: 1_000_000. In a thin market a headline APY is mostly noise, and steering someone with $1k into one is the most plausible real-world harm this server can do. Lower it deliberately, not by accident.

Why get_market_history returns statistics, not just a series

A snapshot cannot tell a durable 6% from a 12% that is a reward programme ending next week. A 180-day standard deviation can. That is the number a 6-month decision actually turns on.

Configuration

env var default purpose
LENDWISE_API_URL https://lendwise.fi Point at http://localhost:3000 to develop against a local lendwise/web.
LENDWISE_INTEGRATION unset Set to 1 to run the network integration tests.

Development

pnpm install
pnpm typecheck
pnpm test                                   # unit tests, hermetic
LENDWISE_INTEGRATION=1 pnpm test            # + live API tests
pnpm build

The one invariant to not break

The optimizer's contract is positional: we send apy: number[], it returns vault_index — an offset into the array we sent, not an id. If the array we build and the array we map back through ever disagree, the server confidently attributes a real allocation to the wrong market, and every number still looks plausible.

Order is therefore established exactly once, from the caller's productIds, and both directions run off that single array (buildApyVectormapAllocations in src/core/optimizer.ts). It is pinned by unit tests in both directions. Do not "simplify" it into a lookup by APY value.

Rate limits

The upstream API allows 60 GraphQL req/min/IP and 10 optimizer req/min/IP. A 429 is surfaced as an explicitly retryable error carrying retryAfterSeconds — back off, don't retry-storm.

Not financial advice

Informational only. APYs are variable and historical yields do not predict future returns.

License

MIT

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured