Lore Context

Name: Lore Context
Author: Lore-Context

by Lore-Contextversion 0.6.0-alpha.1i★ –iRuns on your computer

Registry nameio.github.Lore-Context/lore-context-mcp

Install

Overview

Description from the maker (original English)

Governed AI-agent memory, Evidence Ledger traces, evals, and portable context tools.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: stdio
Category: Accounting, finance & tax
You need to fill in: LORE_API_URL, LORE_API_KEY

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
You fill in yourself: LORE_API_URL, LORE_API_KEY, LORE_MCP_TRANSPORT

Values marked secret are keys to your account. Never share them or paste them into a chat.

You need

npmNode.js installed (for the npx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "lore-context": {
      "command": "npx",
      "args": [
        "-y",
        "@lore-context/server"
      ],
      "env": {
        "LORE_API_URL": "your-value",
        "LORE_API_KEY": "your-value",
        "LORE_MCP_TRANSPORT": "your-value"
      }
    }
  }
}

Run this in your terminal

claude mcp add lore-context --env LORE_API_URL=your-value --env LORE_API_KEY=your-value --env LORE_MCP_TRANSPORT=your-value -- npx -y @lore-context/server

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "lore-context": {
      "command": "npx",
      "args": [
        "-y",
        "@lore-context/server"
      ],
      "env": {
        "LORE_API_URL": "your-value",
        "LORE_API_KEY": "your-value",
        "LORE_MCP_TRANSPORT": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "lore-context": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@lore-context/server"
      ],
      "env": {
        "LORE_API_URL": "your-value",
        "LORE_API_KEY": "your-value",
        "LORE_MCP_TRANSPORT": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

Values you fill in

LORE_API_URL required env
Base URL of the Lore API that the MCP server should proxy tool calls to.
LORE_API_KEY secret env
Optional Lore API key when the API is configured to require authentication.
LORE_MCP_TRANSPORT env
MCP stdio transport implementation. Use sdk unless debugging legacy JSON-RPC mode.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 6, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account Lore-Context, which owns the repo
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Accounting, finance & taxi

More stars than 0% of the other 1720 servers in this category
Published to the registry more recently than 7% of the other 1720 servers in this category
Basic checks equal to or better than 100% of the other 1720 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Lore Context safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

You need to fill in: LORE_API_URL, LORE_API_KEY

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.6.0-alpha.1) reached the registry 6 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js, Docker on your computer.

What can I use instead?

In the same category: Finance Toolkit, SolidInvoice, Korea Tax Calculator

Alternatives

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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

Lore Context

The control plane for AI-agent memory, eval, and governance.

Know what every agent remembered, used, and should forget — before memory becomes production risk.

Getting Started · Website Quickstart · Benchmark Methodology · API Reference · Architecture · Project Plan · Release Status · Roadmap · Integrations · Deployment · Changelog

🌐 Read this in your language: English · 简体中文 · 繁體中文 · 日本語 · 한국어 · Tiếng Việt · Español · Português · Русский · Türkçe · Deutsch · Français · Italiano · Ελληνικά · Polski · Українська · Bahasa Indonesia

Localized docs may lag the current English release notes; the canonical v2.1 docs are the English README and docs/ set.

What is Lore Context

Lore Context is an open-core control plane for AI-agent memory: it composes context across memory, search, repository graphs, and tool traces; evaluates retrieval quality on your own datasets; routes governance review for sensitive content; and exports memory as a portable interchange format you can move between backends.

It does not try to be another memory database. The unique value is what sits on top of memory:

Context Query — single endpoint composes memory + web + repo + tool traces, returns a graded context block with provenance.
Memory Eval — runs Recall@K, Precision@K, MRR, stale-hit-rate, p95 latency on datasets you own; persists runs and diffs them for regression detection.
Governance Review — six-state lifecycle (candidate / active / flagged / redacted / superseded / deleted), risk-tag scanning, poisoning heuristics, immutable audit log.
MIF-like Portability — JSON + Markdown export/import preserving provenance / validity / confidence / source_refs / supersedes / contradicts. Works as a migration format between memory backends.
Repo Graph — deterministic repository indexing (files, symbols, imports, calls, routes, tests) exposed as API routes and read-only MCP tools so agents ground repository answers in a stable project-context contract.
Multi-Agent Adapter — first-class agentmemory integration with version probe + degraded-mode fallback; clean adapter contract for additional runtimes.

When to use it

Use Lore Context when...	Use a memory database (agentmemory, Mem0, Supermemory) when...
You need to prove what your agent remembered, why, and whether it was used	You just need raw memory storage
You run multiple agents (Claude Code, Cursor, Qwen, Hermes, Dify) and want shared trustable context	You're building a single agent and OK with a vendor-locked memory tier
You require local or private deployment for compliance	You prefer a hosted SaaS
You need eval on your own datasets, not vendor benchmarks	Vendor benchmarks are sufficient signal
You want to migrate memory between systems	You don't plan to ever switch backends

Quick Start

# 1. Clone + install

git clone https://github.com/Lore-Context/lore-context.git cd lore-context && pnpm install

2. Run the quickstart helper and inspect the activation report

pnpm quickstart -- --dry-run --activation-report

3. Generate a real API key (do not use placeholders in any environment beyond local-only dev)

export LORE_API_KEY=$(openssl rand -hex 32)

4. Start the API (file-backed, no Postgres required)

pnpm build && PORT=3000 LORE_STORE_PATH=./data/lore-store.json pnpm start:api

5. Write a memory

curl -H "Authorization: Bearer $LORE_API_KEY" -H "Content-Type: application/json" \ -X POST http://127.0.0.1:3000/v1/memory/write \ -d '{"content":"Use RDS as truth store and Qdrant as the derived recall index for Lore Context production.","memory_type":"project_rule","project_id":"demo"}'

6. Query context, then inspect the returned traceId in the Evidence Ledger

curl -H "Authorization: Bearer $LORE_API_KEY" -H "Content-Type: application/json" \ -X POST http://127.0.0.1:3000/v1/context/query \ -d '{"query":"production storage","project_id":"demo","token_budget":1200}'

For the public website quickstart, see lorecontext.com/quickstart. For full setup (Postgres, Docker Compose, Dashboard, MCP integration), see docs/getting-started.md.

The canonical alpha quickstart is git clone + pnpm quickstart. Lore does not currently publish or claim a public @lore-context/quickstart npm package. The MCP stdio server is published separately as @lore-context/server for registry and client distribution, and the SDK middleware ships as @lore-context/sdk-middleware (npm) and lore-context-middleware (PyPI).

For AI-readable discovery, the website publishes /llms.txt and /llms-full.txt from public documentation only. The Official MCP Registry entry is published, and additional distribution drafts live under docs/distribution. Launch drafts live under docs/launch, and design partner intake under docs/design-partners. The public benchmark page is a reproducible methodology and small smoke-run report, not a competitive benchmark-win claim.

Architecture

The diagram below shows the full open-core plus hosted-production shape. In the public OSS repo, local file/Postgres deployment is supported directly; hosted Google sign-in, AWS SQS workers, private embeddings, billing, and multi-tenant operations are commercial hosted-cloud surfaces.

                       ┌───────────────────────────────────────────────┐

MCP/REST clients ─► │ apps/api (auth + rate limit + evidence) │ (Claude Code, │ ├── Memory Inbox / lifecycle / audit │ Codex, Cursor, │ ├── capture ingestion + recall hydration │ OpenCode...) │ ├── context query (memory/web/repo/traces) │ │ ├── repo graph query / symbol / impact │ │ ├── Google sign-in + hosted MCP metadata │ │ └── OpenAPI + usage + operator surfaces │ └───────────────┬───────────────────────────────┘ │ capture / embedding / graph jobs ▼ ┌───────────────────────────────────────────────┐ │ memory-worker (AWS SQS + DLQ fan-out) │ │ ├── auto redaction / curation / save │ │ ├── dreaming butler (prune/merge/resolve) │ │ ├── private Qwen3 embedding service │ │ └── Qdrant dense+sparse indexing │ └───────────────┬───────────────────────────────┘ │ ┌────────────────────┼────────────────────┐ ▼ ▼ ▼ RDS PostgreSQL 16 Qdrant derived index apps/dashboard truth store + audit lore_memories_v12 user-facing SaaS

For detail, see docs/architecture.md.

What's in v2.1.0

v2.1.0 is the Repo Graph API and MCP Tools release. It makes Lore's own repository graph a first-class agent memory surface: deterministic TypeScript/JavaScript repository indexing for files, symbols, imports, calls, routes, tests, and process hints, exposed through API routes and read-only MCP tools so agents ground repository answers in a stable project-context contract instead of ad hoc text search.

v2.1.0 is the current open-core source line. The hosted Lore Cloud production line also runs v2.1.0 on the commercial AWS/Qdrant/private-embedding substrate, but hosted operations, billing, production release automation, and Secret Vault runtime stay in Lore-Context/lore-cloud.

Capability	Status	Where
Repo graph API + MCP tools (`repo.graph_query` / `symbol_context` / `impact` / `detect_changes`)	✅ OSS + hosted production	`packages/repo-graph`, `apps/api`, `apps/mcp-server`
Code knowledge graph indexer	✅ OSS + hosted production	`packages/code-indexer`, `packages/code-indexer-python`
Context Query composing memory + web + repo + tool traces	✅ OSS + hosted production	`apps/api`, `docs/api-reference.md`
7-stream `HybridSearchOrchestrator` (FTS / pgvector / Qdrant dense+sparse / graph / temporal / wiki)	✅ OSS + hosted production	`packages/search`
Cross-encoder reranker (post-fusion, opt-in)	✅ OSS, provider key required	`apps/api/src/rerankers/`
Dreaming butler memory consolidation (prune / merge / resolve / surface)	✅ OSS, flag-gated	`apps/api/src/workers/butler-v18.ts`
Agent memory self-improvement loop + context recipes	✅ OSS, human-gated promotion	`packages/eval`, `packages/search`
SDK middleware (auto-inject + auto-retain for OpenAI / Anthropic clients)	✅ Published	`packages/sdk-middleware-typescript`, `packages/sdk-middleware-python`
Generated SDK source previews	✅ OSS source preview	`packages/sdk-python`, `packages/sdk-go`, `packages/sdk-java`, `packages/sdk-dotnet`
Browser extension capture scaffold	✅ OSS scaffold	`apps/browser-extension`
Secret vault for AI agents (MCP-native, three-button authorization)	Hosted beta, pending crypto audit	commercial runtime in `Lore-Context/lore-cloud`
Cloud Memory Engine: RDS truth store + SQS worker fan-out + Qdrant index	Hosted production	commercial hosted cloud
Private Qwen3-Embedding-0.6B 1024-dim vector service	Hosted production	commercial hosted cloud
Automatic capture ingestion and Memory Inbox exceptions	✅ OSS + hosted production	`apps/api`, `packages/capture`, `apps/dashboard`
Google sign-in + personal vault bootstrap	Hosted production	commercial hosted cloud
Commercial SaaS: individual subscriptions, billing, quota gating	Hosted production	`Lore-Context/lore-cloud`
REST API with API-key auth (reader/writer/admin)	✅ OSS + hosted production	`apps/api`
OpenAPI 3.1 contract at `/openapi.json` (reports `2.1.0`)	✅ OSS + hosted production	`apps/api/src/openapi.ts`
MCP stdio server (legacy + official SDK transport)	✅ OSS + hosted production	`apps/mcp-server`
Next.js dashboard customer workflow scaffold	✅ OSS scaffold + hosted production	`apps/dashboard`
Evidence Ledger API + Dashboard summary	✅ OSS + hosted production	`apps/api`, `apps/dashboard`

| Governance state machine + audit log | ✅ OSS + hosted production | `packages/g

Only the beginning is shown; read the rest in the repo

Lore Context

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

Values you fill in

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Accounting, finance & taxi

Common questions

Alternatives

Finance Toolkit

SolidInvoice

Korea Tax Calculator

README from the maker

Lore Context

What is Lore Context

When to use it

Quick Start

2. Run the quickstart helper and inspect the activation report

3. Generate a real API key (do not use placeholders in any environment beyond local-only dev)

4. Start the API (file-backed, no Postgres required)

5. Write a memory

6. Query context, then inspect the returned traceId in the Evidence Ledger

Architecture

What's in v2.1.0