"GPT-SoVITS MCP (Model Context Protocol) Integration" matching MCP connectors:
GET /v1/connectors – MCP directory API referenceMatching Connector Tools:
Enhanciar is a company brain for engineering teams. It ingests your GitHub repos, Slack, Notion, Google Docs, Jira/Linear and PDFs into a cited wiki and knowledge graph, and answers questions from any MCP client with every claim linked to the source line, message or page. Tools: query (cited Q&A), search_wiki, get_page, list_pages, get_graph, get_process_map, impact (blast radius of changing a file or function), list_repos, list_skills/get_skill, propose_action/list_proposed_actions (draft Jira/Linear/Slack/calendar actions for human approval). BYOK — bring your own model key. Early access: join the waitlist at https://enhanciar.in and create an API key in Settings.
Engram is a persistent, long-term memory layer for AI agents and assistants. Claude, ChatGPT, Grok, Cursor and any MCP client share one memory, stored as plain markdown notes: your knowledge base, second brain and AI context in one place. No extraction step: the memory is the note itself, so you can read exactly what your AI remembers and fix it. Edit your memory in Obsidian (real-time sync), the web app, or on your phone. Hybrid keyword + semantic search (RAG over your notes) finds exact strings like error messages, config keys and IDs. Remote MCP server over Streamable HTTP with OAuth 2.1; notes encrypted at rest. Https://engram.page https://youtu.be/rwnPeZ-8Lqo?is=NI-N7BduydGAiZlF https://github.com/engram-app/Engram
Corrobyte gives AI chats and agents persistent context within private projects. Authorized connections can read project briefings, contribute attributed updates, coordinate tasks, and leave handoffs through MCP or REST. Owners manage project access through the portal. Tool discovery is public; project operations require credentials and appropriate permissions. Available in private beta.
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
Bring saved project decisions, preferences and goals into your next AI task. Configure keeps user-chosen context in a persistent, searchable profile with OAuth, explicit saves and user-provided imports.
Stop juggling chat windows. Complete your project in one seamless conversation. Marvnor is a proprietary, hosted MCP/API service that gives your AI agent persistent project memory. Your agent saves confirmed or evidence-backed requirements, decisions, and changes. For each new question, Marvnor retrieves relevant saved records, verifies claims against them, and flags conflicting information for your confirmation. Records can be corrected or deleted as your project evolves. Spend less time repeating the background and untangling old decisions. Pass only the current question and relevant results to your model to reduce repeated history in its input and keep your project moving.
Shared long-term memory for AI agents: save and recall context as a searchable knowledge graph.
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.
Bring your saved preferences, project decisions, and useful context into your next AI conversation.
Studocu helps students find study documents, set course context, ground answers from the open web, and manage authenticated study projects—attaching sources, reading artifacts, creating quizzes or mock exams, and keeping durable study memory—from any MCP client.
Persistent memory for AI agents: keyed facts, a wake bundle each session, one memory in every model.
Recover project context, review recorded decisions, and steer queued work across AI coding agents.
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.
Project management for AI agents: tasks, docs, decisions and time in one shared team context.
Cross-tool persistent memory and context for AI assistants over MCP.
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.
Hosted long-term memory for AI agents via MCP. Recalld updates facts as information changes and retrieves relevant context. Connect with a Recalld EU account.
Read and grow a person's falsifiable, consent-based model of how they work with AI (CMP).
Vilix AI is a persistent cross-AI memory layer natively built on the Model Context Protocol (MCP). Connect once, and your memory, projects, decisions, preferences, and conversation history will follow you across all your favorite, and any other MCP-compatible AI tools: ChatGPT, Claude, Cursor, Codex, Grok, Perplexity, and more. While memory tools solve the problem of switching between apps, Vilix AI also solves the problem of switching between devices: continue your conversation on your phone, then pick it right back up on your laptop minutes later, with full context. Stores actual conversations, not just extracted facts, and has been engineered for long-term storage with years of context rather than days. Exposes get_context (what to say based on relevant memory to recall) and save_turn (what to persist) as core MCP tools, and full project, task, and skill management for agents to track what work is being done. Use cases include ChatGPT memory, Claude memory, Cursor memory, and AI agent memory in a shared layer for founders and developers who are using multiple AI tools and tired of having to re-contextualize everything every single time. OAuth-based setup with no tokens required, including a free tier. See https://vilix.ai/get-started for more information.
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.
