Contextforge Mcp

io.github.alfredoizdev由 GitHub 账号 alfredoizdev 发布v0.13.3更新于 Nov 7, 2026

Persistent memory MCP server for Claude Code, Cursor, and GitHub Copilot.

概览

AI 生成的概览

ContextForge MCP 通过托管的 ContextForge API,为编程助手提供跨会话的持久可搜索项目记忆、任务跟踪和会话状态。

可以做什么
  • 保存、语义搜索、列出、更正和删除持久记忆,并可对照 git 跟踪的代码检查记忆是否过期
  • 将记忆整理到空间和项目中,并把当前目录关联到某个项目
  • 列出待办任务,并给出接下来该做什么的建议
  • 声明并查看正在进行的编码会话,避免并行会话互相干扰
  • 通过网关工具调用另外 55 项能力:git 同步与历史、快照、导入导出、问题跟踪和协作
适用场景
适合希望助手在 Claude Code、Cursor 或 Copilot 之间跨会话记住决策、架构说明和偏好,并把任务与会话状态集中在一处而非本地文件的场景。
运行要求
通过 npx 以 stdio 在本地运行,需要 Node.js。需要 ContextForge 账号,并通过 CONTEXTFORGE_API_KEY 提供 API 密钥;可用 CONTEXTFORGE_API_URL 覆盖接口地址。需要访问 ContextForge API 的网络。可选的 init 命令会向项目写入规则文件和 Claude Code 钩子。
安装前请注意
记忆、任务和会话数据都存放在 ContextForge 服务端而非本地,API 密钥可访问这些数据。服务器会指示助手主动保存,并把自身视为优先于本地记忆的唯一来源。可选钩子会在本地记录提示词,并在压缩后把会话目标及 git 分支、提交标题和变更文件名作为搜索查询发送出去。可写入、修改和删除记忆。

安装

在 SourceWeft 中

  1. 打开 控制台中的 Contextforge Mcp,将其添加到工作区。
  2. 为需要使用其工具的对话启用该服务。

Desktop only,通过 STDIO。 STDIO 服务会启动本地进程,因此需要 SourceWeft 桌面宿主。

其他 MCP 客户端

参照 仓库 中的启动说明。

README

ContextForge MCP — Persistent Memory for Claude, Cursor & Copilot

[npm version] [License: MIT] [Node.js] [Glama MCP]

Give Claude Code, Cursor, and GitHub Copilot persistent memory across sessions via the Model Context Protocol (MCP). Stop re-explaining your project every time.

ContextForge MCP is an open-source MCP server that connects your AI coding assistants to long-term, searchable memory. Decisions, architecture notes, debugging context, and project knowledge stay available across every session — across every tool that supports MCP.

  • 🧠 Persistent memory — your AI remembers everything across sessions, days, and weeks
  • 🔍 Semantic search — find knowledge by meaning, not keywords
  • 🔗 One memory, every tool — Claude Code, Cursor, Copilot, Claude Desktop, Windsurf
  • 🐙 Git integration — sync commits and PRs automatically
  • ✅ Task tracking — issues, assignments, and project status
  • 👥 Team collaboration — share projects and memory with your team
  • 🆓 Free tier — get started without a credit card

[!NOTE] Works automatically, no config needed (v0.5.1+). On connect, the server sends startup instructions to your AI client. Clients that honor them (Claude Desktop, Claude Code) load your project memory at the start of every session and save new decisions proactively — without you editing any settings. Running init (Step 4) is now a reinforcement, not a requirement, and still helps on clients that don't yet honor server instructions (e.g. Cursor).


Quick Start

1. Install

No install step needed — the setup below runs the server via npx -y contextforge-mcp, which fetches it on demand and keeps it up to date.

Prefer a global install for slightly faster cold starts? npm install -g contextforge-mcp is optional; if you do it, you can drop the npx -y prefix from the commands below.

2. Get your API key

  1. Go to contextforge.dev
  2. Sign up (free tier available)
  3. Settings → API Keys → Generate API Key
  4. Copy your key (starts with cf_)

3. Connect to your AI tool

Claude Desktop

Edit ~/Library/Application Support/Claude/claude_desktop_config.json:

json
{  "mcpServers": {    "contextforge": {      "command": "npx",      "args": ["-y", "contextforge-mcp"],      "env": {        "CONTEXTFORGE_API_KEY": "your-api-key-here"      }    }  }}

Restart Claude Desktop.

Claude Code (CLI)
bash
claude mcp add contextforge -s user \  -e CONTEXTFORGE_API_KEY=your-api-key-here \  -- npx -y contextforge-mcp

Restart Claude Code and run /mcp to verify it's connected.

Cursor

Add to your Cursor MCP settings:

json
{  "mcpServers": {    "contextforge": {      "command": "npx",      "args": ["-y", "contextforge-mcp"],      "env": {        "CONTEXTFORGE_API_KEY": "your-api-key-here"      }    }  }}
GitHub Copilot (VS Code)

Add to your Copilot MCP config:

json
{  "servers": {    "contextforge": {      "command": "npx",      "args": ["-y", "contextforge-mcp"],      "env": {        "CONTEXTFORGE_API_KEY": "your-api-key-here"      }    }  }}

4. Initialize your project (recommended)

With v0.5.1+ the server auto-loads memory on supporting clients (see the note at the top), so this step is optional but recommended: it reinforces the behavior, covers clients that don't honor server instructions, and fully overrides the built-in file-based memory.

Set up your project so your AI editor always prefers ContextForge memory:

bash
npx contextforge-mcp init

By default, init auto-detects which editor your project uses and writes three rule sections and two hooks:

  • Memory rules — route memory questions to ContextForge instead of the built-in file memory
  • Session Presence rules — make parallel sessions check for each other at conversation start and before big changes
  • Startup Context rules — load a short project summary (overview, open tasks, live sessions) from ContextForge at the start of every conversation
  • Post-compaction recall hook (Claude Code only) — a SessionStart hook with matcher compact in .claude/settings.json. When Claude Code compacts a long conversation, the hook runs npx -y contextforge-mcp recall and re-injects the session objective, memories relevant to what you are working on, your project's 10 most recent memories and pending tasks, so decisions saved in ContextForge survive the summary.
  • Session objective hook (Claude Code only, 0.13.0) — a UserPromptSubmit hook that runs the generated script .claude/hooks/contextforge-objective.cjs with plain node (~50 ms). It records your prompts to ~/.contextforge-mcp/sessions/<session_id>.jsonl on your machine, so recall can put the session's objective back after a compaction. The log is pruned after 14 days and never uploaded; see the privacy note below for what recall sends.

Files written:

  • CLAUDE.md for Claude Code (signals: existing CLAUDE.md or .claude/ directory)
  • .cursorrules for Cursor (signals: existing .cursorrules or .cursor/ directory)
  • .claude/settings.json for Claude Code — merged, never overwritten; only the two ContextForge hook groups are added
  • .claude/hooks/contextforge-objective.cjs for Claude Code — the generated objective hook script (safe to commit; refreshed by init when a new version ships; Claude Code's own system turns — prompts that start with an XML-like tag and contain a closing tag — are not logged)

If no editor is detected, both files are generated.

On clients that honor server instructions (Claude Desktop, Claude Code), ContextForge is used automatically even without this step. On other clients — or to guarantee the built-in file-based auto-memory never wins — run init: it writes explicit rules that always route memory to ContextForge.

Override with --editor
FlagBehavior
--editor=claudeGenerate only CLAUDE.md
--editor=cursorGenerate only .cursorrules
--editor=allGenerate both, skip detection

Re-running init is idempotent per section — sections you already have are left untouched; missing ones are appended. Upgrading from an older version? Just re-run npx contextforge-mcp init: it adds the new Startup Context section without touching the rest of your file.

Check your version
bash
npx contextforge-mcp --version   # also: -v, version

Prints the installed version (e.g. contextforge-mcp 0.5.2).

Surviving compaction (Claude Code)

Long sessions get compacted: Claude Code summarizes the conversation to free space, and the summary keeps the gist but drops details — usually the decisions, and often the task itself. init installs two hooks that fix both:

  1. Objective hook (UserPromptSubmit) — records each prompt locally so the session's first real request is never lost to the summary.
  2. Recall hook (SessionStart, matcher compact) — fires right after every compaction and prints back, in this order: the session objective and the latest request before the cut; up to 5 memories relevant to the current work (semantic search over the objective, git branch, recent commit subjects and changed files, whatever their age); the project's 10 most recent memories; up to 5 pending tasks; and a reminder to call memory_query for anything older. The whole block stays around 4 KB and is injected once, never pinned, so it does not move the compaction trigger.

The relevance search is one metered query per compaction. It only runs when there is a session objective or you are on a non-default branch (git-only context on main is noise), it runs in parallel with the other fetches under the same 6-second stage deadline, so a slow search can never drop the rest of the block, and CONTEXTFORGE_RECALL_RELEVANCE=0 in the environment turns it off entirely.

The hooks run as plain shell commands, so recall reads your API key from CONTEXTFORGE_API_KEY if set, otherwise from the contextforge server entry in ~/.claude.json (where claude mcp add stores it), otherwise from a project .mcp.json. It needs a linked project (.contextforge in the repo root). If anything is missing it prints nothing and never blocks the session. Note that a CONTEXTFORGE_API_KEY exported in your shell profile wins over ~/.claude.json: if it holds an old key, recall silently prints nothing.

Try it by hand from your project directory:

bash
npx contextforge-mcp recall           # prints the block for the newest session in this directorynpx contextforge-mcp recall --stats   # local numbers: recalls, objective coverage, follow-up queries

Privacy: the prompt log and the recall stats live under ~/.contextforge-mcp/ on your machine and are never uploaded. What leaves the machine: after a compaction, recall sends the session objective (at most 600 characters, together with the git branch, recent commit subjects and changed file names) to ContextForge as the search query, the same way memory_query sends a query; it is not stored. Note that .claude/settings.json is usually committed, so teammates who pull the repo get the prompt hook too; they can remove the UserPromptSubmit group to opt out.

Already using ContextForge? (existing users)

Nothing to reconfigure. Update to the latest and restart your AI client:

bash
npm update -g contextforge-mcp   # only if you installed globally; npx users get it on next launch

You do not need to re-run init for the auto-load behavior. To get the post-compaction recall hook and the session objective hook, run npx contextforge-mcp init once in each project; it only adds what is missing. Since 0.13.2 the server reminds you once per project when the recall hook is installed but the objective hook is missing or outdated.


Available Tools

ContextForge defines 69 tools across Knowledge Management, GitHub Integration, Issue Tracking, and Collaboration. No capability was ever removed — every tool below is fully callable — but since v0.11.0 your AI client sees only a small subset by default — 15 since v0.13.3 (11 in 0.11.0–0.13.2) (CONTEXTFORGE_TOOLS=lean, the default):

  • 14 core tools — the ten used on the agent's own initiative every session: memory_query, memory_ingest, memory_check_freshness, memory_confirm, memory_correct, memory_forget, tasks_list, tasks_what_next, session_list, memory_help — plus the four that CLAUDE.md / .cursorrules files generated before 0.11.0 call by name, kept visible so those files keep working without re-running init: session_update, memory_current_project, memory_link_project, memory_list_items.
  • cf_tools — one gateway tool that discovers and runs the other 55 (and can reach the core ones too). Ask your AI naturally ("sync my git commits", "restore from a snapshot", "olvida ese recuerdo viejo") and it searches (English or Spanish) and calls the right tool for you — no need to know an exact name.

Set CONTEXTFORGE_TOOLS=full to expose all 69 tools directly to your client instead, matching the behavior of versions before 0.11.0. See Environment Variables.

Why lean by default: 69 tool schemas cost ~15,000 tokens of context on every session, push past Cursor's 40-tool cap, and contribute to the accuracy degradation several clients show past ~50 tools. The lean set cuts that to ~3,500 tokens (~77% less) while keeping every tool one call away via cf_tools.

Knowledge Management

ToolDescription
memory_ingestSave knowledge to memory
memory_querySearch your knowledge semantically
memory_list_itemsList all stored items
memory_deleteRemove specific items
memory_ingest_batchSave multiple items at once
memory_delete_batchDelete items by filter

Spaces & Projects

ToolDescription
memory_list_spacesList your spaces
memory_create_spaceCreate a new space
memory_delete_spaceDelete a space
memory_move_spaceMove space to project
memory_list_projectsList your projects
memory_create_projectCreate a new project
memory_delete_projectDelete a project
memory_link_projectLink directory to project
memory_unlink_projectUnlink directory
memory_current_projectShow linked project

GitHub Integration

ToolDescription
memory_git_connectConnect a GitHub repo
memory_git_listList connected repos
memory_git_activateActivate/deactivate webhook
memory_git_syncImport existing history
memory_git_commitsList synced commits
memory_git_prsList synced PRs
memory_git_disconnectDisconnect a repo

Issue Tracking

ToolDescription
issues_listList your issues
issues_createCreate a new issue
issues_startMark as in progress
issues_resolveMark as resolved
issues_resolve_by_nameResolve by title
issues_assignAssign to collaborator
issues_what_nextGet recommendation

Collaboration

ToolDescription
project_shareShare project by email
collaborators_listList collaborators

Snapshots & Export

ToolDescription
memory_snapshot_createCreate a backup
memory_snapshot_listList all snapshots
memory_snapshot_restoreRestore from backup
memory_snapshot_deleteDelete a snapshot
memory_exportExport to JSON/MD/CSV
memory_importImport from file

Utility

ToolDescription
memory_statsView usage statistics
memory_relateLink two items
memory_helpShow help

Session Presence (multi-session coordination)

Running several Claude Code sessions in parallel (worktrees, agent teams)? Each MCP process automatically registers itself as a live session and heartbeats while it runs. On a clean exit the session is removed at once (a detached helper delivers the goodbye even while the host process is being killed); if the process dies hard, the session expires ~10 minutes after its last heartbeat. Three tools let the agent coordinate — session_list is a core tool and always visible; session_update and session_end are reached through the cf_tools gateway by default (or set CONTEXTFORGE_TOOLS=full to see all three directly):

ToolWhat it does
session_updateDeclare what this session is working on ("working on the auth module")
session_listSee other live sessions in the same project and their focus before touching shared areas (pass all_projects: true for the whole org)
session_endExplicitly end this session's presence (also automatic on exit)

By default session_list is scoped to the current project — where work actually collides. In a multi-project organization, pass all_projects: true to see every session, or project: "<name-or-id>" to scope elsewhere.

Recommended pattern for your CLAUDE.md: call session_list when a conversation starts; call session_update when starting or switching tasks.


Natural Language Examples

You don't need to memorize commands — just talk naturally to your AI:

# Knowledge"Save this: we use PostgreSQL for the main database""What database do we use?""List my spaces"
# GitHub"Connect my repo github.com/myuser/myproject""What commits did I make today?""Show PRs merged this week"
# Issues"Create an issue: Update the login page design""What's pending?""What should I work on next?""Mark the login issue as done"

Environment Variables

VariableRequiredDescription
CONTEXTFORGE_API_KEYYesYour API key from the dashboard
CONTEXTFORGE_API_URLNoAPI endpoint (defaults to production)
CONTEXTFORGE_DEFAULT_SPACENoDefault space for operations
CONTEXTFORGE_TOOLSNolean (default) exposes 15 tools — the 14 core ones plus the cf_tools gateway to the other 55. full exposes all 69, as versions before 0.11.0 did. Lean keeps ContextForge under Cursor's 40-tool cap and Claude Code's 50-tool degradation threshold.

How it works

ContextForge MCP is a thin client that translates Model Context Protocol tool calls into authenticated HTTP requests against the ContextForge API. Your knowledge is stored, indexed (semantic embeddings), and retrieved on the server side — the MCP client itself is stateless.

This means:

  • No infra to manage — no local databases, no embeddings to run, no vector stores to maintain
  • Works everywhere your AI works — same memory across Claude Code, Cursor, Copilot, etc.
  • Team collaboration — shared projects sync in real time

Dashboard

Manage your memory visually at contextforge.dev:

  • View and organize your knowledge
  • Search and filter memories
  • Manage API keys and billing
  • Track issues and collaborate
  • Export and backup data

Development

bash
# Clone and installgit clone https://github.com/alfredoizdev/contextforge-mcp.gitcd contextforge-mcpnpm install
# Buildnpm run build
# Run testsnpm test
# Watch modenpm run dev

Contributing

Issues and pull requests are welcome at github.com/alfredoizdev/contextforge-mcp.


Support


License

MIT © Alfredo Izquierdo

来源:README.md,提交 58706f4

工具

15

memory_ingest

Save to Memory

**Save important context to persistent memory — be proactive.** Call this WHENEVER you learn information that would be valuable in a future conversation: project decisions ('we chose Postgres because X'), architectural choices, user preferences, debugging insights, recurring patterns, deadlines, stakeholder context, or any 'remember this' / 'save this' / 'note that' style request from the user. Heuristic: if you would be sad to lose this fact when the conversation ends, ingest it. Better to over-save than to under-save — the memory_query semantic search will surface what's relevant later. Always pass meaningful `title` and `tags` so the item is discoverable. Set `deduplicate:false` to save even if identical content already exists. **ROUTE BY TOPIC:** pass `space:"<name>"` matching the memory's topic so it lands in the right space instead of the catch-all default. If you don't yet know the project's spaces, call `cf_tools` with query "list spaces" once and reuse the result. Saving without `space:` piles everything into one default space — avoid it in multi-space projects.

输入参数tagstitlecontent必填categoryspace_idsource_urideduplicatesource_typerelated_paths

memory_query

Search Memory

**Search persistent memory BEFORE answering any project-specific question.** You MUST call this tool: (a) at the start of any conversation that touches the user's codebase, work, or decisions, BEFORE generating any response; (b) whenever the user references prior context ('did we', 'we decided', 'remember', 'what did I save', 'last time'); (c) before making architectural or design recommendations — the user's prior decisions live here. Returns semantically relevant stored content. Skipping this when relevant context exists makes you appear to have amnesia and is the #1 reason users abandon persistent memory — always check first, even if you think you remember.

输入参数limitquery必填filtersspace_idmin_scoreproject_idinclude_relationships

memory_list_items

List Memory Items

List all items stored in memory. Shows titles, previews, tags, and creation dates.

输入参数limitoffsetspace_id

memory_help

Memory Help

Show help and usage instructions for ContextForge memory commands

无需输入参数。

memory_current_project

Current Linked Project

**Check the linked project at the start of every new conversation in a directory.** Call this FIRST (alongside memory_query) before answering questions about the user's project, code, or work — it tells you which ContextForge project and spaces are scoped to the current working directory. If `linked: false`, surface that to the user and suggest `memory_link_project`. Pair this with memory_query as your two startup-context calls — they are the cheapest possible way to avoid hallucinating about the user's project.

无需输入参数。

memory_check_freshness

Check Memory Freshness

Check whether memories linked to git-tracked code (via `related_paths` on memory_ingest) are stale because the underlying code changed since they were saved. Compares each candidate's saved commit SHA against the current HEAD with a local `git diff` — no data leaves your machine for the diff itself. Returns up to 3 memories whose related files changed, so you can review and refresh them. Call this periodically or when you suspect saved context might be out of date.

输入参数space_id

memory_confirm

Confirm Memory

Confirm that a memory flagged by memory_check_freshness is still accurate, even though its related code changed. Updates the memory's confirmed timestamp so it won't be flagged again until the code changes further.

输入参数id必填

memory_correct

Correct Memory

Update a memory flagged by memory_check_freshness with corrected content after its related code changed. Replaces the stored content and refreshes the git context (current commit SHA) so future freshness checks compare against the new baseline. For a general edit to any memory that is NOT part of a freshness check, use memory_update instead.

输入参数id必填content必填related_paths

memory_forget

Forget Memory

Delete a memory flagged by memory_check_freshness that is no longer relevant or accurate. Use this instead of memory_delete when acting directly on a freshness check result.

输入参数id必填

tasks_list

List Tasks

**Call this at the start of any conversation about work, planning, or status — and any time the user asks about pending/open/in-progress tasks.** Shows pending tasks by default (sort by due date, urgent first). Use status "all" for everything, "resolved" for completed, "in_progress" for active work. IMPORTANT: Every task includes a dashboard URL (🔗). You MUST include these clickable links when presenting tasks to the user. If you see overdue tasks (past due date), surface them at the top of your response.

输入参数limitscopestatusproject_id

tasks_what_next

What Task is Next?

**Call this whenever the user asks what they should work on, what's next, what's pending, or how to start the day.** Trigger phrases include: 'what should I do', 'where do I start', 'qué hago hoy', 'next task', 'I have time, what's open'. Returns the highest-priority unresolved task assigned to the user, with due date and priority. Always include the dashboard URL (🔗) in your reply so the user can click through. Prefer this over generic answers when the user seems unsure about priorities — it gives a concrete next action.

无需输入参数。

session_update

Declare or update what THIS Claude Code session is currently working on (live presence). Call it when you start or switch tasks so parallel sessions can avoid stepping on your work. Example focus: 'working on the auth module'.

输入参数focus必填label

session_list

List OTHER live Claude Code sessions working on the same project right now, and what each is focused on. By default it is scoped to THIS session's project (the one linked in the current directory) — that's where work actually collides. If the current directory isn't linked to a project, it falls back to the whole organization. Use it at conversation start and before big changes to avoid stepping on parallel sessions. Pass a specific `project` to scope elsewhere, or `all_projects: true` to see every session across the organization. Sessions expire automatically ~10 minutes after their last heartbeat.

输入参数projectall_projectsinclude_stale

cf_tools

ContextForge Tools

Discover and run 55 additional ContextForge capabilities that are not in your tool list: git sync and history, spaces, projects, skills, routines, snapshots, import/export, task editing, and collaboration. If you cannot find a ContextForge capability in your tool list, search for it HERE before concluding it does not exist. Two modes: pass `query` with a plain-language description to search (returns full, ready-to-call schemas of the best matches), or pass `name` plus `args` to run one.

输入参数argsnamequery

版本历史

6
  1. v0.13.3最新Nov 4, 2026
  2. v0.13.2Oct 16, 2026
  3. v0.13.1Oct 16, 2026
  4. v0.13.0Oct 15, 2026
  5. v0.12.0Sep 24, 2026
  6. v0.11.0Sep 16, 2026

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