"Multi MCP (Model Context Protocol) implementation or management" matching MCP servers:

A GitHub-based implementation of the Model Context Protocol that enables LLMs to access and manipulate data in a Universal Object Reference (UOR) framework, providing standardized interfaces for object management with decentralized storage.

Enables AI agents to compose MCP tool calls into Unix-style pipelines, executing complex workflows server-side and returning only the final result.

Autonomous DeFi yield for AI agents on Base. Query APY rates, agent status, payment splits, and referral stats. 4 read-only tools + 1 resource.

Typed MCP gateway for Cork Protocol operations, enabling secure and deterministic interaction with operation core and signing gate.

Enables AI assistants to interact with Square's Connect API through the Model Context Protocol standard, allowing for operations like managing customers, processing payments, and handling inventory.

An MCP server that integrates AI retrievals with NASA's Common Metadata Repository (CMR), allowing users to search NASA's catalog of Earth science datasets through natural language queries.

Access to many public datasets right from your LLM application.

Provides live wait times and office details for all 60 Oregon DMV field offices by scraping the ODOT website, with no authentication required.

Enables AI agents and MCP clients to dispatch queries to the most suitable model among 70+ LLMs by scoring intent, budget, cost, and latency, returning structured routing decisions with execution telemetry. It runs as a zero-dependency Python MCP server that plugs into Claude Desktop, Cursor, and other MCP-compatible clients.

Enables dynamic, intent- and budget-aware routing of queries across 70+ LLMs by balancing cost and latency through Pareto-optimal model selection. Integrates with MCP clients like Claude Desktop and Cursor for automated multi-model execution.

ArcadeDB Multi-Model Database, one DBMS that supports SQL, Cypher, Gremlin, HTTP/JSON, MongoDB and Redis. ArcadeDB is a conceptual fork of OrientDB, the first Multi-Model DBMS. ArcadeDB supports Vector Embeddings.

Enables autonomous agent swarms to coordinate and reach deterministic convergence through epidemic dissemination, causal vector clocks, CRDT reconciliation, quorum-based leader election, and atomic two-phase commit over MCP. It also supports bounded network traffic via rate limiting and conflict-free replication.

A simple MCP server implementation that provides AI models with basic Solana RPC methods and helpful development prompts.

Enables MCP clients to run bounded epidemic dissemination, causal ordering, conflict-free state merging, and quorum-based transaction coordination across autonomous agent swarms.

Provides AI agents with a toolset to query model inventories, trace dependencies, and analyze the impact of changes across machine learning models and data pipelines.

Enables AI clients to create and configure monitors, subscribe to their evidence streams with durable cursors, and process observations with guaranteed at-least-once delivery.

MCP/REST endpoints for token safety scans, honeypot checks, ecosystem stats, and on-chain task rewards.

A plug-and-play solution that enhances AI assistants by enabling them to create projects, manage configurations, and interact with Openfort's wallet infrastructure through 42 specialized tools.

An MCP server that keeps raw tool output out of the context window by sandboxing and compressing results (about 98% reduction), persisting file edits, git operations, tasks and decisions in SQLite with BM25 retrieval so the agent resumes after compaction, and enforcing routing across 17 platforms via MCP and hooks. It also encourages the model to write scripts that compute answers and log only results instead of reading large data into context.

Local MCP server for Bind Protocol — credential parsing, verification, and hashing tools for AI agents.