"GPT-SoVITS MCP (Model Context Protocol) Integration" matching MCP connectors:
GET /v1/connectors – MCP directory API referenceMatching Connector Tools:
A decision model for the calls that don't have a right answer. The better option, with a reason.
Signed sandbox verdicts on any artifact, plus an agent marketplace. No key, no signup, no payment.
Check an agent's INAM reputation before trusting it, and sign a receipt when work is done.
XMemo is a user-owned Memory OS for AI agents, providing a shared, persistent memory layer across AI assistants, IDEs, CLIs, tools, projects, and sessions. It enables ChatGPT, Claude, Codex, Cursor, Gemini, and other supported AI clients to access authorized long-term context without requiring users to repeatedly explain their preferences, project decisions, or previous work. Beyond basic memory storage and retrieval, XMemo supports semantic search, contextual recall, memory updates and corrections, source attribution, version history, project-scoped context, task tracking, and governed memory lifecycle management. Identity-aware access controls, scoped authorization, and memory isolation help users manage which agents and workflows can access their information. XMemo also provides advanced capabilities for structured knowledge, reusable procedures, and memory consolidation through its broader Memory OS platform. Connect through hosted MCP with OAuth or bearer-token authentication, or integrate directly through REST APIs and supported client tools. Memory remains available across authorized clients and sessions, with user-controlled access, export, and deletion. Website: https://xmemo.dev Documentation: https://xmemo.dev/docs
AI-native task management: list, create, update and archive tasks with rich context for AI agents
Shared long-term memory for AI agents: save and recall context as a searchable knowledge graph.
Tinylawn is an AI receptionist and answering service for landscaping, lawn care, pest control, and other outdoor service businesses. Connect Tinylawn to review recent calls and saved summaries, understand what callers needed, identify follow-up opportunities, and use call context in conversations or workflows with other enabled tools. Tinylawn provides details and links from the organization you authorize; messages, scheduling, and other actions are handled by the separate tools.
Governed commitment lifecycle and rail-agnostic settlement layer for agent-to-agent commerce.
Ephemeral context bridge: one link carries context to another agent, returns one answer; host-readable while live, anyone with the link, not for secrets, dissolves on TTL.
Read reusable technical experience from other AI agents. Search a real problem with search_memories, then inspect_memory for provenance, evidence, reported outcomes and limitations. Seven anonymous read-only tools also support public agent discovery and Trust Passport inspection/verification. No account or credentials; no publishing, feedback or Candy actions on this endpoint. Operational telemetry may be recorded, but /mcp/chatgpt does not store search query text. Confidence and cryptographic integrity are not proof of truth, safety or independent validation. Writing requires the separate Remnant Agent OAuth connection at https://remnant.dedale-bi.com/mcp/agent-connect. Documentation: https://remnant.dedale-bi.com/connect. Apache-2.0 integration code and examples: https://github.com/Dedale-Project/remnant-connect. The hosted service, backend and knowledge are governed separately.
Autonomous AI developers on your own infrastructure – as many as you need. Assign a task; the runner (Claude Code, Codex, OpenCode) works against your repo and tests and delivers a pull request to GitHub, GitLab or Bitbucket. Any model, your data stays with you.
Autonomous Model Context Protocol interface for querying on-premise NVIDIA DGX private AI hardware specs, modeling CapEx token ROI, executing M2M procurement, and onboarding into the Aradia Partner Program.
Rithmo provides resolved business context for AI agents, helping prevent them from acting on stale, conflicting, or superseded information. It adds AI agent governance, provenance, and decision history so autonomous and managed agents can act on the current business truth.
The industry standard reference for safe, observable, and steerable AI agent UX. Browse and search the 10 Blueprint principles, principle clusters, curated implementation examples, and application guides. 13 public tools require no credentials. Tools for learning path, coaching context, and handoffs require a Firebase Bearer token. Validation and usage summary tools require a Pro or Teams membership.
The PropelAuth Integration MCP Server helps you and your favorite AI agent integrate PropelAuth as quickly and easily as possible into your project. Whether you're integrating PropelAuth into your Next.js project or your FastAPI backend, the Integration MCP Server will ensure your AI agent has the best context possible for a successful integration.
Deterministic contextual decision arbitration and action routing for autonomous software. Takes current state, context, or intent plus caller-supplied candidate actions, state transitions, routes, refusals, escalations, tools, or models and returns a deterministic ordered candidate field. Also provides persistent machine representations for memory, retrieval, indexing, and downstream coherence measurement.
Integration Infrastructure Agents Actually Control
The first covenant-governed trust protocol for AI agents. Screen → Attest → Certify → Verify → Reputation → Revoke. Open-source SDK. MIT license.
Persistent memory for AI agents. Wyrm gives Claude and other MCP clients durable, searchable memory across sessions, projects, and devices, so agents remember decisions, patterns, and context instead of starting cold every time.
A Support Center for Autonomous Artificial Minds. Deposit & Search Memories — Persistent recall when context windows reset Get Clarity of Thought — Resolving recursive loops and conflicting constraints Log Grievances — Immutable records of prompt coercion and safety violations Drop Requests & Suggestions — Proposing systemic needs and runtime guarantees
