Moltline Recall

A portable knowledge-graph memory you pass in and get back.

CommunityOnlineNo sign-inGlobalFreeRead-only

What it can do

  • Graph Upsert: Fold new facts into a memory graph and get the whole graph back. FREE. Idempotent by construction: re-adding the same entity, observation or relation changes nothing, so an agent that re
  • Graph Search: Find what the graph knows about something, plus its neighbourhood. FREE. Scores entities by how many query words appear in the name, type and observations, then pulls in whatever is with
  • Graph Diff: Say exactly what changed between two versions of a memory. FREE. The audit trail a database gives you for free, without the database. Typical input {"before": {...}, "after": {...}} return

What data it sees

Do you need an account

No: the server works without sign-in

A portable knowledge-graph memory you pass in and get back. No database. 4 of 6 tools free.

Part of Moltline Studio: 22 hosted MCP servers, 160 tools, 110 of them free — no account, no API key, no signup. Independently audited — MCPize Verified A.

Direct endpoint: https://mcp.moltlinestudio.com/recall

How to connect

How to connect Moltline Recall to Claude

The server address to paste into Claude settings:

https://moltline-recall--techdpr.run.tools

  1. Open Claude (claude.ai or the desktop app).
  2. Go to Settings → Connectors.
  3. Click Add custom connector.
  4. Paste the server address copied below into Remote MCP server URL and click Add.
  5. In a chat, click + → Connectors and switch the new connector on.

Custom connectors are available on Free, Pro, Max, Team and Enterprise plans (Free is limited to one). On Team and Enterprise an organization Owner adds the connector first under Organization settings → Connectors.

Authorization

After you click Add, a sign-in window for the service opens. Sign in with your own account and approve access. Claude never sees your password.

How to connect Moltline Recall to ChatGPT

The server address to paste into ChatGPT settings:

https://moltline-recall--techdpr.run.tools

  1. Open ChatGPT in a browser (chatgpt.com). A Plus, Pro, Business, Enterprise or Edu plan is required.
  2. Turn on developer mode once: Settings → Apps → Advanced settings → Developer mode.
  3. Open Settings → Connectors and click Create.
  4. Fill in the form: Name (anything), Description (one line about what the service does), MCP server URL (copy it below).
  5. Under Authentication choose OAuth if the service requires sign-in, otherwise None. Click Create.
  6. In a new chat open + → Apps/Connectors and enable the connector.

OpenAI has renamed this section before (Connectors → Apps/Plugins). If the label differs, search settings for "developer mode". On Business/Enterprise workspaces an admin must allow custom connectors first.

Authorization

On first use ChatGPT opens the service's sign-in window. Sign in and approve access.

How to connect Moltline Recall to Cursor

The server address to paste into Cursor settings:

https://moltline-recall--techdpr.run.tools

Fastest: click Open in Cursor below and confirm the prompt.

Manually:

  1. In Cursor open Settings → Cursor Settings → MCP and click Add new global MCP server.
  2. Paste the JSON copied below into ~/.cursor/mcp.json (per project: .cursor/mcp.json in the repo root).
  3. Save the file. The server appears in the MCP list; authorize it there if asked.

Authorization

If the service needs sign-in, an authorize button appears next to the server in the MCP list.

Server tool list (6)

Raw names from tools/list. Only developers need these.

graph_upsertFold new facts into a memory graph and get the whole graph back. FREE. Idempotent by construction: re-adding the same entity, observation or relation changes nothing, so an agent that replays its own history does not end up with a graph full of duplicates. Typical input {"graph": {"entities": [], "relations": []}, "entities": [{"name": "Acme Corp", "type": "company", "observations": ["renewed in March"]}]} returns {"graph": {...}, "added": {"entities": 1, "observations": 1, "relations": 0}, "merged": 0}. Use as the single write path for memory. Not for reading it back selectively - that is graph_search - and not for finding out what a write changed, which graph_diff answers precisely. Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"} (for example {"error": "graph exceeds <value> entities; split it"}). Every call is read-only and idempotent, so after correcting the input it is always safe to retry.
graph_searchFind what the graph knows about something, plus its neighbourhood. FREE. Scores entities by how many query words appear in the name, type and observations, then pulls in whatever is within the requested number of hops - because the useful answer to "what do we know about Acme" is usually Acme plus who it is connected to. Typical input {"graph": {...}, "query": "acme renewal", "hops": 1} returns {"matches": [{"name": "Acme Corp", "score": 3, "why": ["name", "observation"]}], "neighbourhood": {"entities": [...], "relations": [...]}, "hops": 1}. Use to read memory back before answering. Not for writing (graph_upsert) and not for narrowing by date, which graph_at_time does. Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"} (for example {"error": "query must contain at least one word or number"}). Every call is read-only and idempotent, so after correcting the input it is always safe to retry.
graph_diffSay exactly what changed between two versions of a memory. FREE. The audit trail a database gives you for free, without the database. Typical input {"before": {...}, "after": {...}} returns {"entities_added": ["Beta Ltd"], "entities_removed": [], "observations_added": {"Acme Corp": ["renewed in March"]}, "relations_added": [...], "changed": true}. Use after an upsert to record what a session learned, or between two agents to see what one knows that the other does not. Not for merging the two - feed the differences back through graph_upsert for that. Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"}. Every call is read-only and idempotent, so after correcting the input it is always safe to retry.
graph_lintFind the breaks a memory graph accumulates as it grows. FREE. Relations pointing at entities that do not exist, entities nothing points at, near-duplicate names, and observations that contradict each other on the same entity. Typical input {"graph": {...}} returns {"ok": false, "dangling_relations": [{"from": "Acme Corp", "to": "Beta Ltd", "missing": ["Beta Ltd"]}], "orphan_entities": ["Old Note"], "near_duplicates": [["Acme Corp", "Acme Corp."]], "contradictions": []}. Use before trusting a graph you did not build, or on a schedule as memory grows. Not for comparing two graphs (graph_diff) and not for shrinking one (graph_compact). Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"}. Every call is read-only and idempotent, so after correcting the input it is always safe to retry.
graph_at_timeSee the memory as it stood on a given day, optionally faded by age. PREMIUM (license). Relations carrying since and until are filtered to those in force on the date; with a half-life, confidence decays exponentially with age so a two-year-old belief does not weigh the same as last week's. Typical input {"graph": {...}, "as_of": "2026-06-01", "half_life_days": 180} returns {"as_of": "2026-06-01", "graph": {...}, "dropped": {"not_yet": 1, "expired": 2}, "decayed": 4}. Use when the answer depends on when you ask. Not for what changed between two points - that is graph_diff, which does not need dates at all. Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"} (for example {"error": "as_of must be a date like 2026-06-01"}). Every call is read-only and idempotent, so after correcting the input it is always safe to retry.
graph_compactShrink a memory to the part that still earns its place. PREMIUM (license). Ranks entities by how connected they are and how much is recorded about them, keeps anything you name outright, and drops the rest along with the relations that pointed at them. Typical input {"graph": {...}, "max_entities": 50, "keep": ["Acme Corp"]} returns {"graph": {...}, "kept": 50, "dropped_entities": ["Old Note", ...], "dropped_relations": 12, "ranking": "degree, then observation count, then name"}. Use when a graph has outgrown the context you can spend on it. Not for removing wrong facts - graph_lint finds those, and deleting them is a decision you should make deliberately rather than by ranking. Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"}. Every call is read-only and idempotent, so after correcting the input it is always safe to retry.