apollo-cache-copilot
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@apollo-cache-copilotCheck my Apollo cache for dangling refs and missing typenames"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
apollo-cache-copilot
AI copilot and MCP server for diagnosing Apollo InMemoryCache normalization
defects — built for React Native, where Apollo DevTools does not exist.
The Problem
Apollo Client normalizes every result into a flat map of __typename:id
entities and stores cross-references as { "__ref": "Type:id" } pointers. That
normalization is invisible at write time and only fails at read time — usually
on a screen far away from the mutation that caused it. Three failure classes
dominate, and all three are silent:
Defect | What Apollo does | Symptom |
Orphaned pointer — | Returns | Blank row, no throw |
Missing | Cannot compute a cache key, stores the object inline | Renders fine, then diverges on the second write |
Type/key drift — | Same logical entity under two keys | Duplicated list items, stale reads |
React Native makes every one of them worse:
No Apollo DevTools. The browser extension is the primary cache debugger and it does not exist on RN. The fallback is
console.log(JSON.stringify(client.cache.extract()))and reading a multi-megabyte blob by eye.Persisted cache.
apollo3-cache-persist+ AsyncStorage means a corrupt cache survives app restart — sticky, and reproducing on the user's device only.Offline-first mutations. Optimistic responses write partial entities by design, which is exactly the shape that trips defects 1 and 2.
Long sessions. Mobile apps stay resident for days, so drift accumulates far longer than in a browser tab.
Related MCP server: mcp-rn-devtools
The Solution
Detection is deterministic. Explanation is the model's job.
A cache analyzer that walks
cache.extract()output and reports structural defects with exact paths (User:1.avatar → Avatar:99). Plain graph traversal — no model involved, no guessing, runs on a 10MB snapshot.An MCP server exposing that analyzer to whichever agent the developer is already talking to. The agent asks for findings plus the relevant subgraph, so it never has to hold the whole cache in context.
Diagnosis moves from "paste a 10MB blob and squint" to a conversation.
Architecture
flowchart TD
subgraph client["MCP client — Claude Desktop / Cursor"]
A["Agent (the LLM)"]
end
subgraph server["apollo-cache-copilot (stdio process)"]
T["StdioServerTransport<br/>apollo-copilot mcp"]
R["Tool registry<br/>inspect_dangling_refs<br/>patch_cache<br/>diagnose_cache_graph"]
Z["Zod schemas<br/>parse in, shape out"]
subgraph g["cacheAgentGraph (LangGraph, LLM-free)"]
I["inspectorNode<br/>writes findings"]
RE["reasonerNode<br/>writes proposedPatches"]
P["patcherNode<br/>writes narration"]
I --> RE --> P
end
TOOL1["inspectDanglingRefs()<br/>pure, on a snapshot"]
TOOL2["patchCache()<br/>modify / evict / gc"]
T --> R --> Z --> I
I -.->|calls| TOOL1
P -.->|plans for| TOOL2
end
A <-->|"JSON-RPC 2.0 over stdio"| T
TOOL1 --- CACHE["cache.extract() snapshot"]
TOOL2 --- LIVE["live ApolloCache"]ASCII, same thing:
MCP client (Claude Desktop, Cursor, any stdio client)
│ JSON-RPC 2.0 ▲
▼ over stdio │ stdout IS the protocol channel —
┌─────────────────────────────────┐ all logs go to stderr
│ StdioServerTransport │
├─────────────────────────────────┤
│ tools: inspect_dangling_refs │ read-only
│ patch_cache │ mutating (dryRun available)
│ diagnose_cache_graph │ read-only, plans only
├─────────────────────────────────┤
│ Zod schemas — parse at the edge │
└───────────────┬─────────────────┘
▼
┌─────────────────────────────────────────────────────┐
│ cacheAgentGraph (LangGraph, deliberately LLM-free)│
│ │
│ INSPECTOR ──────► REASONER ──────► PATCHER │
│ walks the store maps findings narrates the │
│ → findings[] → patch ops plan │
│ │ │ │
│ │ owns `findings` │ owns `proposedPatches` │
└──────┼──────────────────┼────────────────────────────┘
▼ ▼
inspectDanglingRefs() patchCache()
pure, on a snapshot cache.modify / evict / gc on a live cacheEach graph node owns exactly one state channel — the inspector writes
findings, the reasoner writes proposedPatches, the patcher writes messages.
Only messages accumulates; re-running a node re-analyzes the same cache, so
appending elsewhere would duplicate every finding on the second pass.
Why no LLM in the graph? Every defect this copilot detects has a mechanical
repair (prune the pointer, evict the orphan). A model would add latency, cost
and nondeterminism to a decision a switch already makes correctly. The graph
earns its keep as orchestration; the model lives in the MCP client, where it
correlates a finding with the mutation or fragment that wrote it.
Installation
npm install @indianic/apollo-cache-copilot
# or, from a checkout
npm install && npm run buildRequires Node.js ≥ 20 (vitest 4 and @langchain/core both require it; CI covers 20 and 22). @apollo/client (v3.8+ or v4), react, and
react-native are peer dependencies — the package uses your app's copies.
Library Usage
ESM only. The package ships types.
inspectDanglingRefs — audit a snapshot
Pure and synchronous. Takes cache.extract() output, returns findings + stats.
import { inspectDanglingRefs } from 'apollo-cache-copilot';
const { findings, stats } = inspectDanglingRefs({
cache: client.cache.extract(),
// all optional:
rootIds: ['ROOT_QUERY', 'ROOT_MUTATION'], // reachability roots
includeUnreachable: true, // report gc candidates
includeNormalizationGaps: true, // report un-keyable inline objects
});
console.log(stats);
// { entityCount: 4, refCount: 3, danglingCount: 1, unreachableCount: 1 }
for (const f of findings) {
console.log(f.kind, f.path, f.danglingRef ?? '');
// ORPHANED_REF User:1.avatar Avatar:99
// UNREACHABLE_ENTITY Post:7
}Finding kinds: ORPHANED_REF, UNREACHABLE_ENTITY, MISSING_TYPENAME,
MISSING_ID. Every finding carries an exact cache path.
patchCache — apply repairs to a live cache
Operations are declarative descriptors so they survive a JSON hop; the tool
rehydrates them into the functions cache.modify wants. Ordered, and failures
are recorded rather than thrown so a bad key mid-batch cannot strand the cache
half-patched.
import { patchCache } from 'apollo-cache-copilot';
const { dryRun, results, collected } = patchCache(client.cache, {
operations: [
// drop dangling refs from a list field
{ type: 'modify', id: 'User:1', fields: { posts: { action: 'PRUNE_DANGLING_REFS' } } },
// delete / invalidate / overwrite a field
{ type: 'modify', id: 'User:1', fields: { avatar: { action: 'DELETE' } } },
{ type: 'modify', id: 'User:1', fields: { bio: { action: 'SET', value: 'unset' } } },
// evict an entity, or one field of it
{ type: 'evict', id: 'Post:7' },
{ type: 'evict', id: 'ROOT_QUERY', fieldName: 'user', args: { id: '1' } },
],
gc: true, // run cache.gc() once, after everything lands
dryRun: false, // true = validate only, cache untouched
});
results.forEach((r) => console.log(r.changed, r.error ?? ''));
console.log('collected:', collected); // keys gc() removedField actions: DELETE, INVALIDATE, SET (with value),
PRUNE_DANGLING_REFS.
cacheAgentGraph — inspect → reason → plan
The compiled LangGraph. Returns findings, the patch operations it would apply,
and per-step narration. It never mutates — feed proposedPatches to
patchCache when you have reviewed them.
import { cacheAgentGraph } from 'apollo-cache-copilot';
const state = await cacheAgentGraph.invoke({ cacheState: client.cache.extract() });
state.messages.forEach((m) => console.log(String(m.content)));
// 2 findings: 1 orphaned ref, 1 unreachable entity.
// ...
// Review, then apply:
patchCache(client.cache, { operations: state.proposedPatches });Also exported: buildCacheAgentGraph() (uncompiled builder), the individual
nodes inspectorNode / reasonerNode / patcherNode, CacheAgentAnnotation,
every Zod schema (InspectDanglingRefsInputSchema, PatchCacheInputSchema, …)
and its inferred type, plus the MCP surface (createServer,
startStdioServer, runInspectDanglingRefs, runPatchCache,
runDiagnoseCacheGraph).
CLI Usage
apollo-copilot [mcp] Start the stdio MCP server (default when no args)
apollo-copilot inspect FILE Diagnose a JSON cache snapshot and print findingsapollo-copilot inspect <file>
Dump the cache from your app, then read it:
// in the RN app
console.log(JSON.stringify(client.cache.extract()));npx -y -p @indianic/apollo-cache-copilot apollo-copilot inspect ./cache-snapshot.json━━ Cache Diagnostic ━━
Entities: 4 | Refs: 3 | Dangling: 1 | Unreachable: 1
⚠ ORPHANED_REF (1)
• User:1.avatar → Avatar:99
Points at "Avatar:99", which is not in the cache. Reads here return undefined.
🗑 UNREACHABLE_ENTITY (1)
• Post:7
No root reaches this entity; cache.gc() would collect it.A clean cache prints ✓ Cache is clean: no findings.
Exit codes: 0 success, 1 unexpected failure, 2 bad input (missing file,
unreadable file, invalid JSON, unknown command).
apollo-copilot mcp
Starts the MCP server on stdio and blocks. Only useful when an MCP client owns
the process — see below. apollo-copilot-mcp is a legacy alias for the same
thing.
stdout is the protocol channel. The server writes nothing but JSON-RPC to stdout; all diagnostics go to stderr. Never add a
console.logto this path.
MCP Setup
Tools exposed
Tool | Input | Behavior |
|
| Read-only. Returns |
|
| Read-only. Runs the full graph. Returns |
|
| Restores the snapshot into a throwaway |
patch_cache carries the snapshot because a stdio server has no live cache to
hand the patcher — only JSON. Diff the returned cache against yours, or
client.cache.restore() it.
Every tool returns both a human-readable summary line and machine-readable
structuredContent, so clients that don't understand structured output still
get the JSON.
Claude Desktop
~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or
%APPDATA%\Claude\claude_desktop_config.json (Windows):
{
"mcpServers": {
"apollo-cache-copilot": {
"command": "npx",
"args": ["-y", "-p", "@indianic/apollo-cache-copilot", "apollo-copilot", "mcp"]
}
}
}From a local checkout — build first (npm run build), then point at the bin
with an absolute path:
{
"mcpServers": {
"apollo-cache-copilot": {
"command": "node",
"args": ["/absolute/path/to/apollo-cache-copilot/bin/apollo-copilot.js", "mcp"]
}
}
}Restart Claude Desktop. The three tools appear under the tools menu.
Cursor
.cursor/mcp.json in the project (or ~/.cursor/mcp.json for every project):
{
"mcpServers": {
"apollo-cache-copilot": {
"command": "npx",
"args": ["-y", "-p", "@indianic/apollo-cache-copilot", "apollo-copilot", "mcp"]
}
}
}Local checkout:
{
"mcpServers": {
"apollo-cache-copilot": {
"command": "node",
"args": ["${workspaceFolder}/bin/apollo-copilot.js", "mcp"]
}
}
}Then Cursor → Settings → MCP → confirm the server is green.
Then just ask
"Here's my cache snapshot — why is the avatar blank on the profile screen?"
The agent calls diagnose_cache_graph, gets User:1.avatar → Avatar:99 plus the
proposed PRUNE_DANGLING_REFS, and correlates it with the mutation that wrote a
reference without the entity body.
Development
npm install
npm run build # tsc -> dist/ (run first: typecheck and tests import dist)
npm run typecheck # tsc --noEmit -p tsconfig.test.json (includes tests)
npm test # vitest runtsconfig.json is the build and excludes __tests__ / __mocks__ so the
published package is just the tools. tsconfig.test.json type-checks
everything and emits nothing.
Success Metrics
# | Metric | Target |
1 | Detection recall on the fixture suite | 100% — every seeded defect found |
2 | False positives on a healthy snapshot | 0 |
3 | Analyzer runtime on a 10MB | < 1s |
4 | Findings carrying an exact cache path | 100% |
5 | Developer time from symptom to named root cause | < 5 min (vs. hours) |
6 | Tokens sent to the model per diagnosis | < 10k — findings + subgraph, never the whole cache |
License
ISC — see LICENSE.
Maintenance
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