Skip to main content
Glama
jarmstrong158

context-keeper-remote

context-keeper-remote

Deploy to Cloudflare

Part of the xylem stack.

A remote MCP server on Cloudflare Workers that exposes context-keeper's rationale store (decisions, pipelines, constraints) over Streamable HTTP. It works as a claude.ai custom connector, including on mobile, so your project's decisions and constraints are available from any Claude session — no PC left running, no tunnel.

Self-host your own copy in a few clicks with the button above — Cloudflare copies this repo into your GitHub account, creates a fresh D1 database for you, and deploys the Worker. Then you add one secret and paste a URL into Claude. Full walkthrough below; every step is a click, no command line anywhere.

The maintainer's own instance runs at https://context-keeper-remote.jarmstrong158.workers.dev. Yours will be at your own subdomain after you deploy.

Why it's built this way

  • Worker, not tunnel — no "PC must be on" dependency.

  • D1, not KV — row-level writes and WHERE queries; two writers (desktop + mobile) don't clobber each other the way whole-file JSON read-modify-write does.

  • Stateless handler, no Durable Objects — the tools are stateless RPCs against D1, so the Worker runs on the Cloudflare free plan.

  • Secret-path auth — claude.ai custom connectors don't reliably send custom bearer headers, so the token is the last path segment of the URL. The URL is the credential.

  • Self-migrating — the Worker creates its own D1 schema at runtime, so a brand-new empty database needs no manual SQL (verified by a cold-start test).


Self-host it (one-click, no command line)

Step 1 — Click "Deploy to Cloudflare"

Click the Deploy to Cloudflare button at the top of this page. Cloudflare will:

  1. Ask you to authorize GitHub and pick an account — it copies this repo into your GitHub account (you get your own repo).

  2. Automatically create a new D1 database in your Cloudflare account and bind it to the Worker. (This works because the Worker's config declares the database binding without a hard-coded id, so Cloudflare provisions a fresh one for you.)

  3. Set up Workers Builds so every push to your new repo redeploys automatically.

  4. Build and deploy the Worker.

When it finishes, your Worker is live at https://context-keeper-remote.<your-subdomain>.workers.dev. Note that URL — you'll need it in Step 3. (You can always find it under Workers & Pages in the dashboard.)

Nothing to configure in the repo, and no SQL to run — the database starts empty and the Worker creates its tables on the first request.

Step 2 — Add the AUTH_TOKEN secret (Cloudflare dashboard)

The Worker refuses every request until it has an auth token, so set one:

  1. Cloudflare dashboard → Workers & Pages → your context-keeper-remote Worker.

  2. SettingsVariables and SecretsAdd.

  3. Type: Secret. Name: AUTH_TOKEN. Value: a long random string (32+ characters — treat it like a password). Save/Deploy.

That value is your connector's password. Keep it somewhere safe; you'll paste it in the next step.

agentsync-remote uses the same AUTH_TOKEN scheme, and additionally needs, in its Worker's Variables and Secrets:

  • a Secret named GH_PAT — a GitHub personal access token, and

  • a Variable named REPO — set to the owner/repo it should sync.

Those two do not apply to context-keeper-remote (this repo) — it only needs AUTH_TOKEN. See the agentsync-remote README for its specifics.

Step 3 — Add the custom connector in claude.ai

  1. claude.ai → SettingsConnectorsAdd custom connector.

  2. Paste your Worker URL with the token as the final path segment:

    https://context-keeper-remote.<your-subdomain>.workers.dev/mcp/<AUTH_TOKEN>

    Replace <your-subdomain> with your Worker's subdomain (Step 1) and <AUTH_TOKEN> with the exact value you set (Step 2).

  3. Save. The tools (record_entry, get_context, query_entries, …) are now available in your Claude sessions.

Check it works: ask Claude to call get_project_summary. If it answers, the whole chain (deploy → auto-provisioned D1 → auto-migration → auth) is working.

Step 4 — Migrate existing local data (optional)

If you already run local context-keeper, ask Claude (with the connector enabled) to call import_entries, pasting each file's contents:

  • decisions.jsonimport_entries(project, kind="decision", entries=[...])

  • pipelines.jsonimport_entries(project, kind="pipeline", entries=[...])

  • constraints.jsonimport_entries(project, kind="constraint", entries=[...])

Incoming ids are preserved; existing ids are reported, never overwritten.


Related MCP server: Remote MCP Server on Cloudflare

⚠️ Security: the connector URL is a credential

The URL you paste into Claude embeds AUTH_TOKEN as its last path segment. Anyone who has the full …/mcp/<AUTH_TOKEN> URL can read and write your entire store. Treat it exactly like a password:

  • Don't share it, screenshot it, or paste it anywhere it could be logged.

  • Requests to any other path, or with the wrong token, get a bare 404 with no detail (a valid token used with a non-POST method gets 405).

  • To rotate: change AUTH_TOKEN in the Cloudflare dashboard (Step 2). This immediately invalidates every old URL — any connector using the previous token starts getting 404s until you update it in claude.ai (Step 3) with the new value.


Tools

Every tool takes an optional project; if omitted it falls back to the configured default_project (set it once with configop='set', key default_project).

The unified tools (config, record_entry) are the current surface; the older per-operation tools remain as deprecated aliases so existing callers keep working. New work should prefer the unified tools.

Tool

Purpose

config

Read or write config: op='get' reads a key, op='set' writes it (value required). Use key default_project (global scope, no project) to pick the project used when a call omits project.

set_config / get_config

Deprecated aliases for config(op='set') / config(op='get').

record_entry

Unified write: record a decision, constraint, or pipeline. Required field depends on kind — decision needs summary, constraint needs rule, pipeline needs name.

record_decision

Deprecated alias for record_entry(kind='decision'): summary, problem, why_chosen, what_we_tried, tradeoffs, tags.

record_constraint

Deprecated alias for record_entry(kind='constraint'): a rule that must hold — rule, reason, tags.

record_pipeline

Deprecated alias for record_entry(kind='pipeline'): a reusable process — name, purpose, steps (extra fields kept verbatim).

get_context

Relevance-ranked retrieval for a query (keyword scoring; excludes deprecated unless include_deprecated).

query_entries

Structured filters: id, kind, tags (all must match), status (active/deprecated/all), free text, and limit.

get_project_summary

One-call orientation: entry counts by kind and status, the ids present, the active constraints (compact), and the most recent decisions.

list_projects

The org registry: every project with entries, plus per-project active counts (decisions/constraints/pipelines), active/deprecated totals, and last-updated time. Enumerates the whole org in one call — discover exact, case-sensitive project names instead of guessing.

update_entry

Merge patch fields into an entry's payload; optionally change status.

deprecate_entry

Mark deprecated, optionally linking superseded_by.

reload_constraints

Compact list of the active constraints.

prune_stale

Delete old deprecated entries (dry run by default; pass dry_run=false).

verify_quality

Flag entries missing rationale-bearing fields.

export_markdown

Render entries as a DECISIONS.md-style document.

import_entries

Bulk import from the local JSON store format (preserves ids, reports collisions, never overwrites).

upsert_entries

Bulk upsert in the local store format — the mirror-sync path. New ids are inserted; an existing id is replaced only when the incoming updated_at is strictly newer (last-writer-wins by timestamp), else skipped. Carries edits and deprecations between mirrored stores; never deletes.

Entry conventions

  • Decisions use summary, problem, why_chosen, what_we_tried, tradeoffs, tags. The deprecated rationale field is accepted on input and mapped to why_chosen when why_chosen is absent.

  • Constraints use rule, reason, tags.

  • Pipelines use name, purpose, steps, plus any extra fields you pass.

  • ids are per project+kind: dec-001, pipe-003, con-012. Because the same id recurs across projects, the D1 primary key is composite (project, id).


For maintainers / contributors

Everything above is for self-hosters. This section is for working on the code itself.

Config layout: how one repo serves both the button and CI

wrangler.toml has two profiles:

  • Default (top level) — the D1 binding is declared without a database_id. This is what the Deploy button, wrangler dev, and the local test suite use. With no id, Cloudflare auto-provisions a fresh database for each self-hoster.

  • [env.production] — pins the maintainer's real database_id and the Worker name. The maintainer's CI deploys with wrangler deploy --env production so it keeps hitting the same database and the same URL. Self-hosters never touch this env.

Deploy pipeline (maintainer only)

.github/workflows/deploy.yml runs on push to main, and is gated with if: github.repository == 'jarmstrong158/context-keeper-remote' so forks (which deploy via Workers Builds instead) don't run failing Actions. Steps: checkout → Node 22 (Wrangler needs ≥ 22) → npm cinpm testwrangler deploy --env production. Tests gate the deploy. It reads two GitHub repo secrets, CLOUDFLARE_API_TOKEN (needs Workers Scripts: Edit) and CLOUDFLARE_ACCOUNT_IDdistinct from the Worker's own AUTH_TOKEN.

Local development

No network and no Cloudflare credentials required — tests run against a local workerd D1 via @cloudflare/vitest-pool-workers. Requires Node ≥ 22.

npm install
npm test          # vitest: migrations, cold-start, CRUD, id sequencing, auth, import, ...
npm run typecheck # tsc --noEmit

Live smoke test

After a deploy, from any machine with network access:

WORKER_URL="https://context-keeper-remote.<subdomain>.workers.dev/mcp/<AUTH_TOKEN>" \
  node scripts/smoke-test.mjs

Runs initialize → tools/list → record_decision → query_entries against the live worker.

Layout

src/index.ts             fetch handler: token check -> MCP dispatch (schema ensured lazily on first tools/call, not on the handshake)
src/mcp.ts               stateless Streamable HTTP MCP server (createMcpHandler)
src/db.ts                D1 access + runtime migration runner + id generation
src/entries.ts           payload normalization, insert-with-retry, keyword scoring
src/tools/*.ts           one module per tool group
schema.sql               reference copy of the DDL the migration runner embeds
wrangler.toml            default (auto-provision) + [env.production] (pinned) config
.github/workflows/deploy.yml   test-then-deploy on push to main (maintainer repo)
scripts/smoke-test.mjs   live JSON-RPC round-trip check
test/                    vitest suite (local workerd D1, no network)

Troubleshooting the maintainer deploy

Symptom in the Actions log

Cause

Fix

Wrangler requires at least Node.js v22.0.0

Node < 22

Already set to Node 22 in deploy.yml.

it's necessary to set a CLOUDFLARE_API_TOKEN environment variable

Deploy secrets missing

Add both GitHub repo secrets.

No route for that URI [code: 7000] / object identifier is invalid [code: 7003]

API token lacks Workers permission, or wrong CLOUDFLARE_ACCOUNT_ID

Use an "Edit Cloudflare Workers" token; confirm the account id.

Deploys succeed but every call returns 404

Worker AUTH_TOKEN not set, or the URL's token doesn't match it

Set/verify AUTH_TOKEN in the Cloudflare dashboard.


  • context-keeper — the local stdio original this Worker hosts as a remote transport.

  • xylem — the stack this is part of.

A
license - permissive license
-
quality - not tested
B
maintenance

Maintenance

Maintainers
Response time
Release cycle
Releases (12mo)
Commit activity

Resources

Unclaimed servers have limited discoverability.

Looking for Admin?

If you are the server author, to access and configure the admin panel.

Related MCP Servers

  • -
    license
    -
    quality
    -
    maintenance
    A Model Context Protocol server implementation that runs on Cloudflare Workers with OAuth authentication support, allowing users to connect MCP clients like Claude Desktop or the MCP Inspector to utilize remote AI tools.
    Last updated
  • F
    license
    -
    quality
    C
    maintenance
    A Model Context Protocol server implementation designed to run on Cloudflare Workers with integrated OAuth authentication. It enables hosting and securely accessing MCP tools remotely via SSE transport from clients like Claude Desktop.
    Last updated

View all related MCP servers

Related MCP Connectors

  • AI Reasoning Cache & Consensus Layer with 11 MCP tools via Streamable HTTP.

  • MCP server for AI agents to plan, verify, and deploy Cloudflare-native apps.

  • User-owned memory for AI agents, Copilot, Claude, IDEs, CLIs, and chat apps over remote MCP.

View all MCP Connectors

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/jarmstrong158/context-keeper-remote'

If you have feedback or need assistance with the MCP directory API, please join our Discord server