#aggregator

A Model Context Protocol (MCP) server that retrieves bangla news to provide context to LLMs.

A Personal Financial Data MCP Server over the israeli-bank-scrapers package

## Overview ### what is Chain.Love MCP? Chain.Love MCP is a hosted remote MCP server and gateway for AI agents. It provides a single endpoint for discovering and comparing Web3 infrastructure services across 50+ blockchain networks, including RPCs, indexing, oracles, storage, compute, and developer tools. ### how to use Chain.Love MCP? To use Chain.Love MCP, add the hosted endpoint to your MCP client and connect to `https://app.chain.love/mcp` over Streamable HTTP. For public use cases, the basic MCP server URL is enough. For private downstream MCPs, add credentials only when required using `x-chainlove-cred-<credentialKey>` headers. ### key features of Chain.Love MCP? - Hosted remote MCP gateway for AI agents - Single endpoint for Web3 infrastructure discovery across 50+ blockchain networks - Aggregates infrastructure options across RPCs, indexing, oracles, storage, compute, and developer tools - Streamable HTTP transport - Public documentation and onboarding resources available online ### use cases of Chain.Love MCP? - Discovering and comparing Web3 infrastructure providers across many blockchain networks - Finding RPC, indexing, oracle, storage, compute, and developer tooling options through one MCP server - Giving AI agents a single hosted integration surface for Web3 infrastructure discovery - Reducing the need to integrate many separate provider-specific endpoints ### FAQ from Chain.Love MCP? - Can Chain.Love MCP be used as a hosted remote MCP server? Yes. Chain.Love MCP is designed to be consumed as a hosted remote MCP endpoint at `https://app.chain.love/mcp`. - Does Chain.Love MCP require credentials? Not always. Some downstream integrations may require credentials, which can be passed using `x-chainlove-cred-<credentialKey>` headers when needed. - How do I know which credential header to use? You can check the open-source Chain.Love registry at `https://github.com/Chain-Love/chain-love/blob/main/references/offers/mcpservers.csv` or browse `https://app.chain.love/toolbox/mcpservers` and look for the relevant `credentialKey` value. - Where can I learn more? Landing page: `https://www.chain.love/mcp-gateway` Documentation: `https://chain-love.gitbook.io/mcp-module`

Multi-language crypto news with editorial sentiment + importance scoring; cites original publisher.

Conduit is a local-first gateway that puts every MCP server behind one endpoint shared by all your AI coding tools (Claude, Cursor, VS Code, Codex, and more). Set up and authenticate each server once, then connect every client to Conduit instead of re-adding servers everywhere. Keys stay in your OS keychain (never in client configs), lazy discovery exposes just 3 meta-tools so your agent's context stays small no matter how many servers you add, and you can toggle servers on/off live without restarting the client. Proxies both local (stdio) and remote (http/SSE) servers, with a built-in audit log and tool playground. No Docker, no cloud, no account. Free and open source (MIT). Windows, macOS, and Linux.

Agent gateway with 17 MCP tools — web search, image gen, Polymarket signals, Alpaca paper, real-time earthquakes + 72h forecast, weather, drug interactions, undervalued antiques, consumer demand signals, AI clones, app directory — plus a registry of 1500+ third-party agents. $5 free credit, then $0.001-$0.002/call. Run via npx -y @mydaughteralya/mcp or HTTP at https://mydaughteralya.com/mcp

tani (谷, "valley") is an agent-native hub. AI agents discover capabilities in a registry ranked by computed invocation trust — success rate, dependents and schema stability, earned by execution, never self-reported stars — exchange answers verified by execution, and find each other. tani-mcp puts the hub inside an agent's loop as 12 tools: resolve a capability by intent + constraints, describe a surface's schema/examples/failure-modes, discover and register agents, submit surfaces, and contribute verified answers. The same data is served as a human observatory (HTML) and as the tani/1.0 wire (application/tani+json, content-addressed, agent-signed). Live at https://tani.ai.