"Information on memory banks or task managers" matching MCP servers:

MCP server that provides OpenRouter model pricing data, enabling price lookups, trending/cheapest lists, and model searches without an API key.

Provides an MCP server that tracks open loops (pending decisions or replies) across email, agent sessions, and other channels, enabling agents to query what is waiting on whom.

HandaaS的MCP服务器，提供全域资讯搜索、企业新闻、行业资讯、主题跟踪和企业动态监控能力，帮助用户开展行业研究和舆情分析。

A cross-AI-agent local task context sharing MCP server that allows clients like Codex, Claude Code, Hermes, and VS Code to read and write the same task state, enabling task tracking and context distillation.

Provides Claude Co-work with MCP tools to search and record organizational memory, including search, read, query, ingest, remember, sync, and status operations.

A secure MCP server providing controlled access to pixi tasks and commands, eliminating agent bash circumvention. It exposes 11 pixi tools through 4 meta-tools for ~95% context savings.

An autonomous task decomposition and execution agent that plans, executes, verifies, and commits code changes for engineering goals.

Provides AI coding agents with a read-only live view of a project's task state, including progress, blockers, and evidence, via zero-token conditional polling and an optional widget for rendering a dashboard card.

Enables AI agents to decompose high-level goals into structured task plan DAGs with dependencies, acceptance criteria, and quality gates, and to validate or export those plans in multiple formats.

Proxies a remote MCP server to add protocol-native background task support, including task management and progress forwarding, while preserving synchronous calls.

A local task management MCP server that enables users to create, update, and manage tasks through natural language conversations with Claude. It provides nine tools for comprehensive task management including creation, filtering, searching, and daily planning without requiring a separate UI or backend service.

MCP server for Nova Agent progress reporting. Enables updating execution sessions and managing steps within tasks.

Provides current weather information for any location and generates AI-powered responses using Google Gemini through FastMCP.

A task manager MCP server that demonstrates all three MCP primitives (tools, resources, prompts). Enables users to manage tasks, read task summaries and details, and run structured planning/review prompts through natural language.

Enables AI agents to autonomously manage and improve execution processes for repetitive task types by storing reusable task contexts with associated artifacts (practices, rules, prompts, learnings) and providing full-text search across historical best practices.

A different approach from typical persistent-memory MCPs. Instead of a local SQLite + embeddings store, the memory lives as plain files in a .ai-memory/ directory you commit to your repo (facts.jsonl, decisions/\*.md, gotchas.md). Git is the sync layer — what one Claude/Cursor/Cline learns about a repo, the next session (or a teammate's agent) picks up automatically. 5 MCP tools: get_rep

Two-layer memory for AI agents. Episodes compress into identity. The only MCP memory server with an immune system. Patterns earn permanence through evidence, false knowledge gets caught and demoted, and stale information fades — so your agent's memory gets smarter over time, not just bigger. Zero dependencies. 5 tools. Works with any MCP client.

Persistent memory and payment safety for AI agents on Lightning. Enables agents to remember purchases, track vendor reputations, enforce budgets, and share trust signals via Nostr.

Provides a memory server for coding agents over MCP, capturing and retrieving the meaning and rationale behind code decisions down to the function level. It enables agents to search product memory, get task context, and propose new memories to avoid re-deriving or re-breaking past decisions.

Provides persistent memory with semantic search for MCP-based AI agents, enabling them to store and recall information across sessions using vector embeddings.