"Threads" matching MCP servers:

An MCP server that exposes Threads CLI data for managing hierarchical threads, containers, and progress logs. It enables users to create, organize, and track task history while maintaining compatibility with the Threads CLI storage.

A stdio MCP server for the official Threads API, enabling publishing, reading, moderation, insights, discovery, locations, and setup diagnostics.

Enables MCP clients to create, read, message, wait for, interrupt, and settle persistent peer threads through an existing T3 Code server, keeping them visible across its clients. It supports project-scoped coordination with source attribution and retry-safe commands.

Thread Contract is a local runtime contract layer for AI coding-agent threads. It lets users pin explicit, thread-scoped rules without turning them into project policy or long-term memory.

Markdown collaboration for AI workflows. Share markdown via public links with four permission levels, inline comments, and real-time sync. AI agents can read docs, review comments, incorporate feedback, and resolve threads. Free, no login.

Provides read-only access to Jira, enabling users to retrieve issue details, comment threads, linked-issue context, epic children, and JQL search results as compact Markdown.

Local code review for people and their coding agents: an agent opens a review of its changes and hands over a link, the person comments on lines, and the agent reads the threads, replies and resolves what it fixed. Reads the git worktree directly, uncommitted work included; nothing leaves the machine.

MCP server that reduces token consumption in AI coding assistants by up to 90% via structural reads, PreToolUse hooks, and tp-\* subagents.

Enables an agent to create and message other Codex sessions on the same host through the running App Server, including resuming and continuing sessions in Desktop.

Enables MCP-compatible coding harnesses to read Amp threads as Markdown, with pagination and filtering options, through a read-only interface.

A shared coordination layer for multiple AI coding assistants, exposing a persistent task queue, per-task message threads, and progress tracking via JSON files on disk.

Enables multiple AI coding tools to collaboratively review code by sharing a SQLite-backed board, allowing them to create threads, post and reply to comments, list threads, and update statuses through MCP.

Provides read-only Codex consultation tools over MCP, enabling fresh threads, continuation, and project reviews via local stdio.

MCP server for profiling Java applications via JDK utilities (jcmd, jfr, jps). Enables AI assistants to diagnose performance, analyze threads, and inspect JFR recordings without manual CLI usage.

Structures AI conversations into hierarchical thread trees, replacing full history with concise summaries to reduce token consumption and preserve context.

Enables management of GitHub pull request review threads through natural language, allowing users to list, reply to, and resolve PR review comments using GitHub's GraphQL API.

Сonnects to live JVMs via JDWP protocol, enabling LLM agents to autonomously debug Java applications — attach to a running process, pause threads, set breakpoints (including conditional), inspect stacks with auto-resolved object fields, evaluate methods, set variable values, and diagnose issues like deadlocks and hung queries.

Enables an MCP client to drive the merge-request review workflow on a self-hosted GitLab CE 11.3 instance: list and create merge requests, read per-file diffs, post comments on exact diff lines, reply to and resolve threads, and merge. It also exposes read-only helpers for projects, branches, files, users, labels, pipelines and an escape-hatch raw API call, honoring a read-only mode.

Enables sharing coding progress on Twitter by analyzing sessions and generating tweet suggestions, with tools for posting tweets, threads, and OAuth authentication.

An MCP server that enables interaction with Twist workspaces using the Twist REST API, allowing users to manage their Twist inbox by viewing, archiving, unarchiving, and marking threads as read.