"Apache Solr" matching MCP servers:

The accountability layer for AI agents — a named human's signed yes before an agent does anything irreversible (payment, record change, deploy), then an offline-verifiable Trust Receipt. Apache-2.0, formally verified.

Local one-shot YAML/JSON agent workflow CLI with tools, approvals, and resume, plus an optional stdio MCP server. Apache-2.0, BYOK.

Open-source framework for AI agents (Claude Code, Cursor, Codex, Gemini) to autonomously operate Google Ads, Meta Ads, and Search Console. Grounded in a local STRATEGY.md — not metric-chasing. Defense-in-depth security, local-first. Apache 2.0.

Tamper-evident local memory + governance MCP for Claude Code, Cursor and Codex. Free, Apache-2.0. Ships the Claude Code Seatbelt Kit.

Enables AI assistants to directly control, automate, orchestrate, and self-heal Hybris/CCv2 environments and headless Spartacus storefronts through 27 JSON-RPC tools. Covers greenfield site provisioning, CMS scaffolding, B2B organization governance, Drools promotion rules, Solr reindexing, catalog sync, FlexibleSearch/ImpEx/Groovy execution, Spartacus diagnostics with auto-fix, and a self-evolving script and knowledge library.

Manage and monitor Hadoop clusters via Apache Ambari API, enabling service operations, configuration changes, status checks, and request tracking through a unified MCP interface for simplified administration. * Guide: https://call518.medium.com/llm-based-ambari-control-via-mcp-8668a2b5ffb9

Open-source AI teammates for your company. The self-hosted agent layer: build, run and govern AI agents on your own servers, models and rules. RAG, skills, a real browser, 4,700+ MCP servers and an API, with budgets, approvals and an audit trail. Apache-2.0, built on Pydantic AI.

The Wanaku MCP Router stands between autonomous AI agents and your enterprise systems. Wanaku leverages proven integration technology, like Apache Camel, to set up and manage hundreds or thousands of integrations.

Enables users to inspect database schemas, validate SQL syntax, and execute queries against PostgreSQL and Apache Hive through standardized Model Context Protocol tools for safe query generation and validation.

Enables AI agents to manage and interact with Apache AGE graph databases through natural language. Supports creating, updating, querying, and visualizing multiple graphs with vertices and edges.

Local-first MCP Work Model for coding agents: retrieves scored memory, records commitments, and credits outcomes from tests, reviews, replies, or owner approval. Public repo includes Apache-2.0 integration glue; the local engine binary is proprietary.

Agentic AI instruction encoding. 86.8% smaller than JSON. Inference-free decode by table lookup. 342 opcodes, 26 namespaces, three conformant SDKs. Confirmed over LoRa mesh radio. Apache 2.0 with express patent grant.

Sovereign, encrypted, persistent memory for AI agents. Eight MCP tools — remember, recall, forget (GDPR Art. 17 erasure), share, governance. Anchored on COTI V2 mainnet. Apache-2.0.

A tool that converts natural-language requests into full, deployable, execution-verified Apache Flink SQL jobs by orchestrating an LLM to draft specs, generate Flink SQL, and verify correctness against real Flink clusters and streaming semantics—including windowed aggregates, joins, Kafka grounding, and Deployable pipelines via the generate_flink_job, ground_kafka_topic, and deploy_to_kafka tools.

An MCP server that enables a supervising OpenAI Codex agent to delegate bounded implementation tasks to isolated worker threads with enforced file scopes and verification, optionally running in parallel git worktrees.

Carbon-aware MCP scheduler that defers "do it later" / "by tomorrow" / "overnight" LLM tasks to the cleanest electricity-grid hour inside a deadline — 40-70% lower CO2 per task, 50% cheaper via Anthropic/OpenAI Batch APIs. 9 MCP tools, per-task carbon receipts to local SQLite, Apache-2.0.

Exposes 79 cybersecurity skills and 12 orchestrator agents over MCP, with a typed 11-field output contract, an enforced resolvable-evidence gate (no verdict without a resolvable source), and human-approval gating for every mutating action. Apache-2.0, stdlib-only.

Unchallengeable AI agent security audits. MASSAT framework covers all 10 OWASP Agentic Security categories (ASI01-ASI10); audit score 4.3/10 published publicly. Plus the trust layer for the x402 agent economy: ERC-8004 passports, ProofDB delegation chains, on-chain anchoring, x402 + Fedimint payments. Apache-2.0.

Integrates SOAR (Security Orchestration, Automation and Response) capabilities into AI clients, enabling security playbook execution, event management, and threat intelligence queries. Provides a complete security incident response platform through natural language interactions.

Integrates Security Orchestration, Automation and Response (SOAR) platform capabilities into AI clients like Claude Desktop and Cherry Studio. Enables users to execute security playbooks, manage security events, and perform automated threat response through natural language interactions.