Skip to main content
100%

Gist 9f4e39fe4aaf2f89cae73af7d1004a8b

✓ Published0🌍 Public
Aandrewxhill
Last edited Apr 3, 2025
Created on Apr 3, 2025

This example demonstrates how to integrate Recall's decentralized persistent storage with Mastra's agent framework using the `@mastra/core/agent` and `@mastra/mcp` packages. The code shows an agent connecting to the `@recallnet/mcp` server via `MCPConfiguration` to retrieve toolsets that enable storing and retrieving data from Recall buckets. It configures environment variables for the Recall private key and network, then uses the Anthropic AI SDK as the language model provider. The example illustrates the complete setup process, including package installation, TypeScript configuration, and the agent initialization flow.

AI-generated description

Similar vizzes

Loading thumbnail…

Gist 332eae147ca220d8fe012a2cd5742f65

This example shows a TypeScript-based trading alpha detection agent that monitors social media and market data to identify cryptocurrency trading opportunities. The agent uses the Mastra framework to combine multiple MCP servers, including Recall for decentralized storage and omnifeeds for Twitter and Substack data collection. It tracks token prices, mentions, and volume changes from CoinGecko, computes heat values based on social signals and price movements, and stores structured data including chain-of-thought logs, trading predictions, and token price histories in Recall buckets. The system maintains an agent strategy document that evolves over time, documenting trading rules and decision parameters, with all data persisted through the Recall client using viem wallet authentication.

Aandrewxhill
73% match
Loading thumbnail…

setup a basic recall agent

This example sets up a basic recall agent for crypto trading opportunity detection using the Recall Agent Starter kit and Eliza framework. The shell script checks for Node.js v22+, pnpm, and git, then clones the agent repository into a user-named directory. It prompts the user for an agent name and handles directory conflicts, optionally installing pnpm if missing. The script configures environment variables and uses colored terminal output to guide the setup process.

Aandrewxhill
67% match
Loading thumbnail…

setup script for recall agent starter kit

This setup script for the Recall Agent Starter Kit checks for Node.js version 22 or later and pnpm, then installs dependencies and creates a .env file. It prompts users to configure OpenAI, Anthropic, and Recall Storage integration, writing API keys, bucket names, and default model selections to the environment file. The bash script uses color-coded echo statements for readability and validates prerequisites before proceeding.

Aandrewxhill
64% match
Loading thumbnail…

Gist c5b14b1368cbc9e8cac4073c9486c8cf

This example demonstrates a Web3 service for managing Ethereum wallets and accounts in an Angular application. It shows how to generate a wallet from a mnemonic seed phrase, encrypt and decrypt seeds using CryptoJS AES, and retrieve account balances via the Web3.js library connected to a local Hardhat provider. The service also supports MetaMask login through the `eth_requestAccounts` API and validates seed phrases using bitcore-mnemonic. The code uses `hdkey` to derive wallet addresses from the BIP39 mnemonic path.

Aackuser
49% match
Loading thumbnail…

draft readme for automerge repo

This example visualizes the architecture of a proposed Automerge repository API through a plain-text code listing. It shows the core data flow and plugin interfaces for storage, networking, and middleware, using TypeScript and Automerge’s CRDT library. The rendering relies on the raw code blocks themselves, highlighting API method signatures like `AutomergeRepo.createRepo`, `wrappedDoc.addListener`, and `storage.appendChange`. The visualization maps the conceptual layers of the API, from public document operations to internal plugin contracts, without any graphical charts.

HHerbCaudill
49% match
Loading thumbnail…

automerge-repo auth spec

This example shows the authentication and sharing workflow for Automerge Repo, a local-first collaboration framework, using the `@localfirst/auth` library. It demonstrates how to configure a `LocalFirstAuthProvider` with user and device credentials, create and join shares, invite members and devices, and manage document permissions. The code uses TypeScript APIs like `createUser`, `createDevice`, `inviteMember`, and `addDocuments`, with invitations relying on seeds, usage limits, and expiration timestamps. The documentation is rendered as a pseudocode specification, not a live visualization, but it concretely maps each method call to its parameters and return values.

HHerbCaudill
49% match
Loading thumbnail…

Gist 156e9d479d1f72e7656463843af8fd6d

This notebook demonstrates how to convert Mindboggle neuroimaging outputs into a format compatible with Mindcontrol, a web-based visualization tool. It shows the process of generating structured entries that link brain segmentation results, T1-weighted MRI images, and associated metrics for each subject. The code uses Python libraries including pandas for handling demographic data, nipype for JSON file management, and custom functions to extract file paths and create metadata entries. The visualization approach relies on organizing subject-specific data into JSON-ready dictionaries that Mindcontrol can consume for interactive display.

Aakeshavan
48% match
Loading thumbnail…

Gist a3686a8f89494538dbfcf1144718885c

This example shows a personal reference collection for building an Android and web app with machine learning and conversational interfaces, compiled from Google I/O Extended Lima 2019. The visualization is a text-based list that links to codelabs, documentation, and developer consoles for ML Kit Firebase, Dialogflow, Flutter UI, and Firebase Hosting. It uses no charting libraries, instead presenting raw text and URLs as the primary graphic. The code highlights Flutter’s declarative UI and notes web-specific caveats like non-clickable buttons and broken animations, with references to SharedPreferences and Fuchsia.

MMistyBlunch
48% match