LangChain is a framework for developing applications powered by language models, providing tools and components to build context-aware, reasoning applications that integrate with external data sources.
Enforces authorize-before-execute for any MCP-compatible AI agent. Exposes atlasent_evaluate and atlasent_verify_permit tools so a protected tool call only runs after AtlaSent issues and verifies a signed, single-use permit — fail-closed on any error, timeout, or malformed response.
8
45
333 npm
Apache 2.0
Why this server?
Allows connecting agents to Metis governed memory as a retrieval source via LangChain, alongside remote MCP and a Python client.
Metis gives AI agents expert know-how that named reviewers have approved, and only where its recorded conditions match the situation. High-risk situations go to a person. When an agent sees practice depart from procedure, it can send the expert one short question. Every retrieval is recorded on a hash-linked evidence chain.
6
10
359 PyPI
2
Apache 2.0
Why this server?
Provides security and hallucination inspection for LangChain agent pipelines, with attestation verification.
Zero-trust safety & settlement rail for autonomous AI agents. Sub-10ms deterministic guardrails, secret leak defense, bounded wallet controls, and on-chain Proof-of-Safety attestations via x402.
14
9
2
MIT
Why this server?
Integrates with LangChain, enabling LangChain agents to use MCP tools for querying options market structure, signals, and levels from Trading Volatility.
Enables AI agents to discover and retrieve options market-structure data (GEX, gamma flip levels, dealer positioning, skew, max pain, expected-move levels, options flow, and ranked trade setups) from Trading Volatility's public API via natural language.
17
1
MIT
Why this server?
Provides LangChain-based AI agents with tools to observe, operate, and govern GPU clusters.
VibOps MCP is the control plane between your AI agents and your GPU infrastructure. 74 tools covering: GPU fleet management (deploy, scale, monitor across NVIDIA, AMD, Intel, AWS, Google, Groq), Agent Infrastructure Control Plane (per-agent GPU cost, budget enforcement, model policies, dependency graph), governance (AI Act, SOC 2, immutable HMAC audit chain), and GPU FinOps (chargeback, waste..)..
74
18
MIT
Why this server?
Compatible with LangChain agents as MCP clients for browser automation and end-to-end testing
Zero-Config, Fully AI-Managed End-to-End Testing for all code gen platforms.
8
441 npm
68
Apache 2.0
Why this server?
Provides seamless integration with the LangSmith observability platform, enabling language models to fetch conversation history, manage prompts, retrieve traces and runs, work with datasets and examples, and access experiment and evaluation data from LangSmith projects.
Enables language models to access LangSmith observability platform features including fetching conversation history, managing prompts, retrieving traces and runs, working with datasets and examples, and analyzing experiments.
13
46,108 PyPI
131
MIT
Why this server?
Integrates with LangChain agents via MCP adapters, enabling fleet knowledge retrieval, conservation checks, and ternary validation in LangChain workflows.
Enables Claude Code to query and control the SuperInstance fleet, including fleet status, conservation law checks, semantic search, and agent registry.
8
10 npm
MIT
Why this server?
Provides LangChain agents with tools to search and verify MCP servers.
