"Ways to make money" matching MCP servers:

A money-in-politics knowledge graph, as an MCP server. It links entities across federal campaign donations, lobbying disclosures, and government contracts.

Long AI conversations fail in predictable ways. Context-First fixes all four: Failure Mode What Goes Wrong Context-First Solution Context Drift AI forgets earlier decisions and intent as the conversation grows context_loop + detect_drift continuously re-anchor every turn Silent Contradiction New inputs silently overrule established facts — the AI doesn't notice detect_conflicts compares every inp

Provides OpenCode with adaptive long-term memory by storing preferences, lessons, and usage history locally in SQLite, enabling AI to remember and adapt to users through context-based learning.

Make it easy for agents to build their context about your projects over time The server provides a set of tools to help agents accumulate knowledge about a project over time in a structured way.

Turn Obsidian notes into agent-ready context, preview-only plans, and safe repo handoffs.

Enables users to read, search and edit GEDCOM (.ged) family-tree files from Ancestry.com and other genealogy software, letting an MCP client navigate relationships, explore ancestor and descendant trees, inspect sources and citations, and make safe, lossless edits that are written straight back to the file with a backup.

Enables AI agents to use an approved session to inspect capabilities, manage projects and memories, perform bounded reads, and make journaled changes through a stdio interface.

Make AI apps answer your way, check with you before acting, and get approvals on your phone.

Gives AI apps a shared, plain-folder memory on your own machine, so whatever you tell one model the others can read, and you can inspect, review and undo every change they make. Memory stays portable across vendors, models and account changes instead of living on a provider's servers.

Enables AI assistants to make phone calls via CallZero service, with tools for call management, templates, and memory.

Provides a local-first memory layer for coding agents, storing principles, rules, and corrections on-device and surfacing them at the moments they apply so agents act on the intended outcomes without sending data to the cloud.

Enables AI agents to store and retrieve memories with user-specific context using Mem0, allowing them to maintain conversation history and make informed decisions based on past interactions.

Enables an AI agent over MCP to read, file, and correct a plain-file, self-hosted personal life store — memories, people, money, body, papers, decisions and someday, alongside the usual tasks, projects, goals, habits and areas — recording every edit and deliberate non-edit so it can be reviewed and reversed. The agent does the maintenance work; the user just visits to glance at what needs them or wander through what's there.

Enables building and querying a Markdown-based knowledge graph with hybrid vector, keyword, and graph retrieval, community detection, and evidence-grounded answers through isolated workspaces.

Enables MCP clients to add, search, and delete persistent namespace-scoped notes through a local stdio server backed by a SQLite database. Namespaces isolate queries and content-derived IDs make repeated writes idempotent.

Enables MCP clients to search, read, create, and link notes in a local-first Markdown vault, with indexing, backlinks, and safe writes underneath.

Enables agents to query and append shared memory in a local, user-owned Markdown/Obsidian vault through hybrid vector and keyword retrieval with reranking, while redacting secrets and PII into sanitized, minimum-viable briefs. It also dispatches approved tasks to Wajo Fo's MCP endpoint over StreamableHTTP or SSE and writes execution receipts back to the vault.

Enables LLMs to make section-level edits to a self-hosted XWiki instance by patching one section's body while reconstructing the full page for the single write call XWiki exposes, with version-conflict protection against concurrent changes.

Local-first semantic memory server with project indexing for AI assistants. It enables AI assistants to store, retrieve, and search memories and project code using embeddings and vector search.

🧠 High-performance persistent memory system for Model Context Protocol (MCP) powered by libSQL. Features vector search, semantic knowledge storage, and efficient relationship management - perfect for AI agents and knowledge graph applications.

Enables AI agents to make outbound phone calls, send SMS, and transcribe recordings via Twilio, while also giving them searchable memory over past Claude Code, Codex CLI, and Cursor sessions stored in local SQLite.

Gives your AI a live picture of your home bar's spirits, liqueurs, juices, garnishes, equipment and glassware, so it can suggest cocktails you can actually make right now, propose substitutes, help use up open bottles before they turn, and keep a shopping list. Runs locally alongside a web UI where you and the AI read and write the same inventory, with fill levels, expiry dates and every change logged.

Enables agents to access a shared portable vault for memory, skills, and API credentials through MCP, so tools can store and retrieve memories, read versioned skill playbooks, and make server-side API calls without exposing secret keys.

Combines bm25, vector and knowledge graphs to create a comprehensive memory solution. https://github.com/lumetra-io/engram-memory-mcp

Enables MCP-compatible agents to read explicitly specified persona files, long-term memories, daily summaries, and valid continuation cards through read-only context tools. It supports keyword recall and limited source retrieval with source numbering and eligibility re-checks.

Turns GitHub repository history into a cited maintainer skill for coding agents, providing tools to collect evidence, query the knowledge graph, and inspect bundles.

Enables coding agents to query a local, versioned knowledge graph of a software project, retrieving overviews, context packs, evidence, and explanations to make informed changes.

Provides read-only access to the Family Office Knowledge Graph, enabling resolution of family offices, retrieval of public records with provenance, and listing of events, aliases, and nodes.

Serves instructions and templates that make any AI coding tool plan before building, work through a project checklist in the right order, and hold a consistent standard, while all reading and writing of your code stays on your machine.

Enables Claude to act as a personal assistant in Telegram by providing tools to read new messages, send replies, and manage tasks/reminders/notes in a Supabase-backed memory.