Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
作者による説明(英語の原文)
Local-first intent and provenance for Codex, Claude Code, Cursor, Gemini CLI, and MCP agents.
この3つを1つのスコアにまとめることはしません。意見、測定、人気はそれぞれ別のものだからです。
このサーバーのやさしい解説はまだ書いていません。以下はレジストリから読み取った事実です。
使っているAIアプリを選んで、設定をコピーしてください。
必要なもの
どのアプリを使っていますか?
上でアプリを選んでください。選んだアプリを覚えておくので、次からはボタンに「…にインストール」と表示されます。
Claude Desktop → Settings → Developer → Edit Config を開き、claude_desktop_config.json にこれを貼り付けます
{
"mcpServers": {
"pathmark": {
"command": "npx",
"args": [
"-y",
"pathmark"
]
}
}
}ターミナルでこれを実行します
claude mcp add pathmark -- npx -y pathmarkプロジェクトの .cursor/mcp.json、または ~/.cursor/mcp.json に貼り付けます
{
"mcpServers": {
"pathmark": {
"command": "npx",
"args": [
"-y",
"pathmark"
]
}
}
}ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。
プロジェクトの .vscode/mcp.json に貼り付けます
{
"servers": {
"pathmark": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"pathmark"
]
}
}
}ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。
これはパソコンで動くサーバーですが、ChatGPTがつなげるのはインターネット上のサーバーだけです。ほかのアプリを選んでください。
選んだアプリは、この端末のCookieに保存されます。アカウントは不要です。
この設定は、作者のレジストリ登録情報から作成しています。READMEと違う場合は、READMEに従ってください。
パソコンで動くサーバーです。インストールすると、ツール一覧がAIアプリに表示されます。
誰でも見られる情報をチェックしており、コードは読んでいません。当てはまらない項目は数に入れていません。 · 2026年11月6日にチェック
レジストリ名は、リポジトリを所有するGitHubアカウント hacksurvivor で確認済みです
このリポジトリはまだGitHubから読み取っていません
このリポジトリはまだGitHubから読み取っていません
これはパソコンで動くため、インターネット上のエンドポイントはありません
パソコンで動き、代わりにローカルの設定を使います
パソコンで動くサーバーです。ツール一覧を読み取れるのは、インターネット上のエンドポイントがある場合だけです
レジストリでこのカテゴリにある有効なすべてのサーバーと比較しています。スターは、公開者がリポジトリの所有者である場合だけ数えます。
当てはまる基本チェック1項目のうち1項目に合格しました。コードは読んでいません。キーやトークンを追加する前に、サーバーがどんなアクセスを求めているかを確認し、必要な権限だけを持つキーを使ってください。
レジストリには必須のキーは載っていません。ただし、最初に使うときにサインインを求めるサーバーもあります。
あなたのパソコンで動きます。必要なときにAIアプリが起動し、データは作者のサーバーを通りません(サーバー自体がオンラインサービスを呼び出す場合を除きます)。
GitHubリポジトリの最終更新は–、最新バージョン(0.1.17)がレジストリに届いたのは39 日前です。
Claude Desktop、Claude Code、Cursor、VS CodeなどのMCP対応アプリで使えます。パソコンにNode.jsも必要です。
同じカテゴリには:Spec Driven Development, Remote Desktop Commander, zanadir
同じカテゴリで、ほかの作者が作ったサーバー。スターの多い順。
カードの見方:★ GitHubスターi3つの柱:レビュー · チェック · 利用状況i更新=最新バージョンをレジストリに公開した日i
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
Find what a repository's CI is missing, and which security checks cannot fail the build.
作者のリポジトリから書かれたとおりにコピーしたものです。PopNx MCPは内容を確認・推奨していません。HTML、画像、スクリプトは取り除いています。リンクはこのサイトの外へ移動します。
Carry intent across agents without turning stale code facts into hidden memory.
Pathmark v0.1.17 stops Claude Code from gating every memory lookup:
pathmark setup claude-code --apply-permissions adds allow rules for Pathmark's ten local read-only tools, so recall and search run without a permission prompt, and in auto mode without a safety-classifier round-trip that can fail transiently;~/.claude/settings.json, adds only missing rules, keeps every other setting, and never rewrites a file it cannot parse;readOnlyHint/openWorldHint annotations, so anything that writes, deletes, or may call an external model always keeps its prompt.See the v0.1.17 release notes or the complete changelog. The npm badge above always shows the currently published version.
Pathmark gives Codex, Claude Code, opencode, Gemini CLI, Cursor, and any MCP-capable harness one local intent and provenance layer. Save decisions, constraints, preferences, and approved conclusions once. Use them from the next agent without pasting a recap.
Code remembers implementation. Pathmark remembers intent. Repository code, architecture, tests, CI, and intentional agent instructions remain authoritative for how the software works. Raw sessions are searchable evidence, not automatically trusted truth.
Your context stays on disk at ~/.pathmark/memory/memory.jsonl. You do not need an account, hosted database, API key, or vendor backend to start.
Pathmark is a Developer Tools submission for OpenAI Build Week 2026. The project existed before the challenge, so the submission is deliberately scoped to the meaningful extension built after the submission period opened on July 13, 2026.
During the eligible period, Codex with GPT-5.6 helped audit and extend Pathmark from a working local memory layer into safer long-running developer infrastructure:
The primary Codex session for this work is 019f5fc3-d7e6-7b41-8a30-d161c90b98fb. The qualifying release range is v0.1.6 through v0.1.7; the pre-challenge baseline is commit 4c0e87dfdbd2ba4c643abd8b887cc228bdb08b73.
See the Build Week implementation record for the before/after boundary, commit evidence, Codex collaboration details, and a fast judge test.
You do not work in one tool. You ask Codex to patch, Claude Code to review, opencode to clean up, and Gemini CLI to challenge the plan. Each tool starts cold unless you carry the context across.
Pathmark gives those tools one place to read and write intent and evidence:
remember, search_memory, recall_memory, session_trace, rate_recall, consolidate_memory, audit_memory, and conclusion-first chat / ask_memory.Pathmark stays provider-neutral. Codex gets one optional synthesis preset. The core server works with any MCP client that can use local tools.
Pathmark requires Node.js 22.5 or newer.
You switch tools during a coding session:
Pathmark keeps the notes in one store.
Point each harness at the same store:
Codex \
Claude Code \ opencode > Pathmark MCP > ~/.pathmark/memory/memory.jsonl Gemini CLI / Cursor /
Install Pathmark in each harness and point them at the same PATHMARK_STORE_DIR. One tool saves raw context with remember or proposes a durable conclusion with create_conclusion; an approved conclusion and raw evidence can then be recovered with recall_memory, search_memory, get_context, or ask_memory.
Pathmark sits below the agents as an intent, evidence, and provenance bus for your coding workflow.
Pathmark exposes these MCP tools:
| Tool | Purpose |
|---|---|
remember | Save raw searchable evidence. Raw evidence is not treated as durable approved intent. |
create_conclusion | Propose a higher-signal durable conclusion or preference. Approval is required by default before recall. |
search_memory | Search memories and conclusions. |
recall_memory | Transparent recall: returns context plus the exact memory IDs, timestamps, sources, matches, tags, and previews used. Accepts optional tags, exact ids, and compact includeRecords: false output. |
session_trace | Return a bounded chronological audit trail for one session: prompts, exact injected memory IDs, redacted tool inputs/results, and answers. |
rate_recall | Label exact IDs from a chat / ask_memory recall as relevant or irrelevant so audit precision is measured. |
get_context | Return compact context for a task or question. |
list_conclusions | List approved saved conclusions. |
list_pending_conclusions | Review bounded, paginated pending conclusion proposals. |
approve_conclusion | Atomically approve a proposal, optionally correcting text/tags and recording the reviewer. |
reject_conclusion | Retain a rejected proposal in the audit trail while permanently excluding it from recall. |
get_memory_snapshot | Generate a bounded USER/PROJECT/AGENT snapshot from approved canonical conclusions. |
consolidate_memory | Review a bounded unsynthesized evidence batch and optionally stage evidence-backed proposals. Nothing is auto-approved. |
delete_memory | Soft-delete a memory or conclusion by id. |
update_memory | Correct a record while preserving prior versions. |
supersede_memory | Replace an outdated record with a linked current record. |
purge_memory | Preview or apply permanent deletion by id, namespace, tags, source, or date. |
audit_memory | Measure capture-to-recall behavior, unused records, recall age, duplicates, stale raw hits, and whether precision labels exist. |
doctor_memory | Report duplicates, deleted/expired records, conclusions, and index health. |
compact_memory | Preview or apply deduplication, retention, and physical cleanup with an automatic backup. |
backup_memory | Create a point-in-time canonical JSONL backup. |
export_memory | Export a scoped mergeable JSONL bundle, optionally encrypted. |
ask_memory | Return an approved-conclusion answer or scoped raw context, exact provenance, and a recall ID for feedback. |
chat | Chat-compatible alias for ask_memory, including multi-intent conclusion retrieval and explicit abstention. |
get_config | Show local store configuration. |
npm install -g pathmark
Then add the MCP server to your client.
Prefer npm for normal installs. To test the current GitHub main branch directly:
npm install -g --install-links=true github:hacksurvivor/pathmark
Generate a setup snippet for your harness:
pathmark setup list
pathmark setup claude-code pathmark setup opencode --json pathmark setup gemini-cli pathmark setup kimi
See docs/compatibility.md for Codex, Claude Code, opencode, Gemini CLI, OpenClaw, Hermes Agent, Grok CLI, Kimi, GLM, and generic MCP setups.
codex mcp add pathmark -- pathmark
Codex users can also enable auto-capture:
pathmark codex install --replace-legacy-hooks
When you want the visible "what memory did you use?" entry in Codex, Claude Code, Cursor, opencode, Gemini CLI, Grok-compatible MCP hosts, or any other MCP harness, call the recall_memory tool before answering. Codex session start injects an approved conclusion snapshot. Before non-trivial prompts, Codex recalls approved conclusions first and uses fresh scoped raw evidence only as a bounded fallback. recall_memory remains the portable visible trace across harnesses.
claude mcp add --scope user pathmark -- pathmark
pathmark setup claude-code --apply-permissions
The second command lets Pathmark's local read-only tools (recall, search, diagnostics) run without a permission prompt, including in auto mode, where they would otherwise wait on the safety classifier. It backs up ~/.claude/settings.json, adds only the missing allow rules, and leaves everything else untouched. Tools that write or delete memory still ask.
--scope user makes Pathmark available in every project; Claude Code's default scope only covers the current directory. For automatic capture and session-start recall (including after context compaction), merge the hooks block from pathmark setup claude-code into ~/.claude/settings.json.
Claude Code's built-in auto-memory lives in per-project folders the other agents cannot see. Bring it into the shared store as evidence (re-runnable; edits update in place with history, and records you delete in Pathmark stay deleted):
pathmark import-native claude-code --dry-run
pathmark import-native claude-code
Use the generated snippets:
pathmark setup opencode
pathmark setup gemini-cli
Add this to your Claude Desktop MCP config:
{
"mcpServers": { "pathmark": { "command": "pathmark", "env": { "PATHMARK_STORE_DIR": "~/.pathmark/memory" } } } }
Add the same command to Cursor's MCP server settings:
{
"mcpServers": { "pathmark": { "command": "pathmark" } } }
npm install
npm test npm run coverage
Run directly:
PATHMARK_STORE_DIR=.pathmark npm run dev
Pathmark can import a compatible local JSONL memory store without deleting or moving the source files.
npm run import:legacy -- --source-dir ~/old-codex-memory
Defaults:
Legacy source: ~/.pathmark/legacy/codex
Pathmark target: ~/.pathmark/memory/memory.jsonl
The importer creates a memory.jsonl.backup-* file before writing, uses deterministic ids so reruns skip duplicates, and redacts obvious KEY=..., TOKEN=..., PASSWORD=..., and Bearer ... values. It uses the same store lock as live MCP and Codex writers, so an import cannot overwrite records captured concurrently.
Use a dry run fir
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