Search Results for "context" - Page 6
Sort By:
Showing 887 open source projects for "context"
View related business solutions-
$300 Free Credits to Build on Google CloudPut your $300 in credit toward real workloads, then keep building with free monthly usage for 20+ products. No commitment and no charge until you upgrade.
-
Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
-
1
LlamaIndex
Central interface to connect your LLM's with external data
...It provides the following tools in an easy-to-use fashion. Provides indices over your unstructured and structured data for use with LLM's. These indices help to abstract away common boilerplate and pain points for in-context learning. Dealing with prompt limitations (e.g. 4096 tokens for Davinci) when the context is too big. Offers you a comprehensive toolset, trading off cost and performance. -
2
Telegram MCP
MCP server to work with Telegram through MTProto
An MCP server that bridges the Telegram API and AI assistants, enabling seamless interaction between AI applications and Telegram through MTProto. -
3
firerpa LAMDA
The most powerful Android RPA agent framework
lamda is an Android RPA agent framework that provides visual remote desktop control and automation at scale, geared toward testing, automation validation, and device management. It exposes a clean UI to monitor and interact with connected devices and includes tooling to script actions reliably across apps and OS versions. The project emphasizes low-friction setup and powerful control primitives so teams can move from interactive validation to repeatable automation. A public wiki, releases,... -
4
Pal
A personal context-agent that learns how you work
...The system acts as an AI-powered “second brain” capable of capturing, organizing, and retrieving personal knowledge such as notes, bookmarks, research findings, people, and meeting information. Instead of acting as a simple chatbot, Pal continuously builds a structured database of a user’s knowledge and context so it can answer questions, recall information, and assist with future tasks more effectively. The agent can perform web research, summarize information, and store insights so that useful discoveries are not lost across conversations or sessions. Over time, the agent learns from interactions, remembers patterns that worked well, and applies those learnings to similar tasks in the future, allowing it to improve without requiring additional model training. -
Demo Series - Small Business Backup By VeeamWatch this on-demand demo series and learn how to protect your Microsoft 365 data with clear, simple, actionable steps that are easy to implement for businesses of all sizes.
-
5
MCP Linear
MCP server that enables AI assistants to interact with Linear project
The MCP Linear server is a Model Context Protocol (MCP) implementation that enables AI assistants to interact with the Linear project management system through natural language. It allows users to retrieve, create, and update issues, projects, and teams within Linear, facilitating seamless integration between AI models and project management workflows. -
6
MCP Kibela
MCP server implementation that enables AI assistants
The MCP-Kibela server is a Model Context Protocol server implementation that enables AI assistants to search and reference content stored in Kibela. This integration allows AI models to securely access information within Kibela, enhancing their contextual understanding and response generation. -
7
Contentful MCP
MCP (Model Context Protocol) server for the Contentful Management API
The Contentful MCP Server is an MCP server implementation that integrates with Contentful's Content Management API, providing comprehensive content management capabilities. It allows AI assistants to interact with Contentful, facilitating tasks such as content retrieval and management. -
8
MCP Server Amazon Bedrock
Model Context Procotol(MCP) server for using Amazon Bedrock
The Amazon Bedrock MCP Server is an MCP server that integrates with Amazon Bedrock's Nova Canvas model for AI image generation. It allows users to generate high-quality images from text descriptions using Amazon's AI capabilities. -
9
MCP WebResearch
MCP web research server (give Claude real-time info from the web)
The MCP Web Research Server is a Model Context Protocol server designed to bring real-time web information into AI applications like Claude, facilitating efficient research on any topic. -
Host LLMs in Production With On-Demand GPUsDeploy your model, get an endpoint, pay only for compute time. No GPU provisioning or infrastructure management required.
-
10
MCP Monitor
A system monitoring tool that exposes system metrics
The MCP System Monitor is a tool that exposes system metrics via the Model Context Protocol (MCP), allowing Large Language Models (LLMs) to retrieve real-time system information through an MCP-compatible interface. -
11
EVM MCP Server
MCP server that provides LLM with tools for interacting with EVM
EVM MCP Server is a comprehensive Model Context Protocol (MCP) server that provides blockchain services across multiple EVM-compatible networks. It enables AI agents to interact with Ethereum, Optimism, Arbitrum, Base, Polygon, and many other EVM chains through a unified interface. -
12
MCP Claude Code
MCP implementation of Claude Code capabilities and more
The MCP Claude Code server implements Claude Code-like functionality, allowing AI assistants to directly execute instructions for modifying and improving project files. It leverages the Model Context Protocol for seamless integration with various MCP clients. -
13
Rust Docs MCP Server
Prevents outdated Rust code suggestions from AI assistants
The Rust Docs MCP Server fetches documentation for specified Rust crates, generates embeddings for the content, and provides an MCP tool to answer questions about the crate based on the documentation context. -
14
Airtable MCP
Airtable integration for AI-powered applications
Airtable MCP is an integration tool that enables AI-powered applications to access and manipulate Airtable databases directly from the IDE using Anthropic's Model Context Protocol (MCP). It allows querying, creating, updating, and deleting records using natural language, facilitating seamless data management. -
15
MCP Snowflake Server
A Model Context Protocol (MCP) server implementation
An MCP server implementation that facilitates database interactions with Snowflake, allowing execution of SQL queries and presentation of data insights as resources. -
16
MongoDB Lens
MongoDB Lens: Full Featured MCP Server for MongoDB Databases
MongoDB Lens is a local Model Context Protocol (MCP) server offering full-featured access to MongoDB databases using natural language via large language models (LLMs). It enables users to perform queries, run aggregations, optimize performance, and more through conversational interactions. -
17
MCP BigQuery Server
A Model Context Protocol (MCP) server that provides secure
This MCP server provides secure, read-only access to BigQuery datasets, enabling large language models (LLMs) to safely query and analyze data through a standardized interface. -
18
K8s MCP Server
K8s-mcp-server is a Model Context Protocol (MCP) server
An MCP server that enables AI assistants like Claude to securely execute Kubernetes commands, providing a bridge between language models and essential Kubernetes CLI tools for cluster management and deployments. -
19
MCP Teams Server
An MCP (Model Context Protocol) server implementation
An MCP server implementation for Microsoft Teams integration, providing capabilities to read messages, create messages, reply to messages, and mention members, facilitating AI-driven interactions within Teams. -
20
Google Calendar MCP
Google Calendar MCP server for Claude Desktop integration
A Model Context Protocol server that allows AI assistants like Claude to interact with Google Calendar, enabling seamless calendar management through natural language conversations. -
21
Kimi-K3
Open Frontier Intelligence
...Its design combines Kimi Delta Attention, gated multihead latent attention, Attention Residuals, and Stable LatentMoE routing. The model can process text and images and supports a context window of more than one million tokens. It is built for long engineering sessions, large repository navigation, tool orchestration, research, visualization, and other extended tasks. The repository publishes the model overview, technical report, evaluation results, architecture specifications, and open weights under the Kimi K3 License. -
22
Tutti
Where people and agents build in tune
Tutti is an open-source shared workspace for people working with multiple AI agents. It is built to reduce the copy-paste handoff problem between tools such as Claude Code, Codex, Canvas, and other agent systems. The workspace connects context, files, app outputs, conversations, and running tasks so agents can build on each other’s work. Users can reference previous conversations, files, tasks, and app results directly instead of re-explaining the project state. Tutti also includes an app center for design, images, documents, presentations, and other workflow outputs. ... -
23
MCP Server Azure DevOps
An MCP server for Azure DevOps
The Azure DevOps MCP Server is an MCP server implementation that allows AI assistants to interact with Azure DevOps APIs through a standardized protocol. It facilitates access and management of projects, work items, repositories, and more. -
24
Fast Jev Compaction
Claude Code plugin that replaces the compaction summary
...The system progressively reduces oversized context before scoring it and falls back to Claude Code’s built-in compaction when necessary. It is designed to preserve exact paths, errors, commands, and constraints that ordinary summaries might lose. -
25
MemMachine
Universal memory layer for AI Agents
MemMachine is a universal memory layer designed for AI agents that provides persistent, rich memory storage and retrieval capabilities so autonomous agent systems can recall context, personal preferences, and long-term interaction history across sessions, models, and use cases. Unlike ephemeral LLM prompt state, MemMachine supports distinct memory types—short-term conversational context, long-term persistent knowledge, and profile memory for personalized facts—persisted in optimized stores (e.g., graph databases for episodic lines of reasoning and SQL for user facts) to support robust, context-aware intelligence in agents. ...
