Back to Browse

June MCP Server

Developer ToolsModerate5.2MCP RegistryLocal
Free

Server data from the Official MCP Registry

Shared, cited knowledge-graph memory for agents — ask, search, and remember against a June endpoint

About

Shared, cited knowledge-graph memory for agents — ask, search, and remember against a June endpoint

Security Report

5.2
Moderate5.2Moderate Risk

june-mcp is a well-architected MCP connector with strong security practices. Authentication is required (API key + canvas binding), credentials are handled safely via environment variables and request headers, and permissions appropriately match the connector's purpose as a thin knowledge-graph client. Minor code quality observations exist but do not constitute security vulnerabilities. Supply chain analysis found 5 known vulnerabilities in dependencies (0 critical, 5 high severity). Package verification found 1 issue.

5 files analyzed · 10 issues found

Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.

Permissions Required

This plugin requests these system permissions. Most are normal for its category.

env_vars

Check that this permission is expected for this type of plugin.

HTTP Network Access

Connects to external APIs or services over the internet.

File System Read

Reads files on your machine. Normal for tools that analyze or process local data.

What You'll Need

Set these up before or after installing:

Your June endpoint, e.g. http://localhost:8000 (the Junê desktop app's local engine, your own june-local service, or a hosted Team workspace)Optional

Environment variable: JUNE_BASE_URL

The canvas (workspace) to bind this connection to — a name (e.g. 'work') or a canvas id; names resolve at startup and ambiguous names fail closedOptional

Environment variable: JUNE_CANVAS

Your June API key (set JUNE_ALLOW_ANON=1 instead to explicitly opt out for keyless local setups)Required

Environment variable: JUNE_API_KEY

Bring-your-own LLM key for cited answers — forwarded per-request as a header, never logged or stored on the serviceRequired

Environment variable: JUNE_LLM_KEY

Set to 1 to create the named canvas on first run if it doesn't exist yet (refused in read-only mode)Optional

Environment variable: JUNE_CANVAS_CREATE

Set to 1 to hide and refuse all write tools (memory becomes read-only)Optional

Environment variable: JUNE_READONLY

Opt-in directory agents may upload files from via june_ingest_file — unset means that tool doesn't existOptional

Environment variable: JUNE_FILES_ROOT

How to Install

Add this to your MCP configuration file:

{
  "mcpServers": {
    "io-github-junemind-june-mcp": {
      "env": {
        "JUNE_CANVAS": "your-june-canvas-here",
        "JUNE_API_KEY": "your-june-api-key-here",
        "JUNE_LLM_KEY": "your-june-llm-key-here",
        "JUNE_BASE_URL": "your-june-base-url-here",
        "JUNE_READONLY": "your-june-readonly-here",
        "JUNE_FILES_ROOT": "your-june-files-root-here",
        "JUNE_CANVAS_CREATE": "your-june-canvas-create-here"
      },
      "args": [
        "june-mcp"
      ],
      "command": "uvx"
    }
  }
}

Documentation

View on GitHub

From the project's GitHub README.

june-mcp

Give your agent a memory. june-mcp is the official MCP server for Junê — it connects any MCP host (Claude Desktop, Claude Code, and friends) to a June knowledge graph, so your agent can ask, search, and remember against a shared, cited, tenant-isolated memory.

This package is a thin, zero-logic connector: all retrieval, graph assembly, and answering happen on the June endpoint you point it at. No engine code lives here — which is why it's small enough to read in one sitting.

Claude Desktop / Claude Code  ──stdio──▶  june-mcp  ──HTTPS──▶  your June endpoint
                                                                 (graph · retrieval · answers)

Install

pip install june-mcp          # just the connector   (or: pipx install june-mcp)
pip install june-ai           # umbrella: june-mcp + june-bench (the benchmark suite)
pip install "june-bench[mcp]" # the bench, with the connector as an extra

Point it at a June endpoint

june-mcp speaks to any June service. Three ways to have one:

  1. Junê desktop app (local-first). Run the Junê app and connect to its local engine — your files, graph, and keys stay on your machine.
  2. Your own June service. Pro/Team customers running the june-local engine package point JUNE_BASE_URL at their own server.
  3. Hosted (Team). Point at your hosted June workspace endpoint with the API key from your console.

Configure

The server is fail-closed: it refuses to start unless it knows where to connect and as whom, and tells you everything that's missing in one message (not one error at a time).

envrequiredmeaning
JUNE_BASE_URLYour June endpoint, e.g. http://localhost:8000
JUNE_CANVASThe canvas (workspace) to bind this connection to — a name (work) or a canvas id. Names resolve to the id at startup; ambiguous names fail closed
JUNE_CANVAS_CREATEoptional1 creates the named canvas on first run if it doesn't exist yet (refused in read-only mode)
JUNE_API_KEYYour June API key (JUNE_ALLOW_ANON=1 explicitly opts out for keyless local setups)
JUNE_LLM_KEYoptionalBring-your-own LLM key for cited answers — forwarded per-request as a header, never logged, never stored on the service
JUNE_READONLYoptional1 hides + refuses all write tools (memory becomes read-only)
JUNE_FILES_ROOToptionalOpt-in directory agents may upload files from via june_ingest_file — unset ⇒ that tool doesn't exist
JUNE_TIMEOUT_READ / JUNE_TIMEOUT_ANSWERoptionalPer-verb timeouts (defaults 15 s / 120 s)
JUNE_LOG_LEVELoptionalLogging is stderr-only by design — stdout is the MCP wire

Check it before your agent does

JUNE_BASE_URL=http://localhost:8000 JUNE_API_KEY=... JUNE_CANVAS=work june-mcp --doctor

The doctor verifies, in order: config → service reachable → canvas resolution (your canvas name → its id, e.g. name "work" → 9147bee6-…) → search seam healthy → tool manifest, and prints PASS/FAIL per check with a mapped hint (e.g. a missing name lists the canvases that DO exist and points at JUNE_CANVAS_CREATE=1). The doctor exits 0 only when every check passes (1 otherwise); the server itself exits 2 on a config error instead of starting half-wired. Run the doctor first; it catches every common misconfiguration before your agent ever sees the server.

Wire it into Claude

Claude Desktop — merge into claude_desktop_config.json (Settings → Developer):

{
  "mcpServers": {
    "june": {
      "command": "june-mcp",
      "env": {
        "JUNE_BASE_URL": "http://localhost:8000",
        "JUNE_API_KEY": "your-key",
        "JUNE_CANVAS": "work",
        "JUNE_LLM_KEY": "your-llm-provider-key"
      }
    }
  }
}

Claude Code:

claude mcp add june -e JUNE_BASE_URL=http://localhost:8000 \
  -e JUNE_API_KEY=your-key -e JUNE_CANVAS=work \
  -e JUNE_LLM_KEY=your-llm-provider-key -- june-mcp

Fully restart the host (Cmd+Q on macOS), then check the server shows 10 tools (11 when you opt into june_ingest_file via JUNE_FILES_ROOT).

The tools

toolwhat your agent gets
june_answerA grounded, cited answer from the graph — abstains rather than guesses
june_searchRanked evidence for a query (supports multi-hop)
june_contextAn assembled context pack under a token budget
june_neighborhoodThe graph around one node
june_subgraphA bounded subgraph export
june_rememberWrite a fact/note into the graph (becomes retrievable + citable immediately)
june_ingestStructured node/edge ingestion
june_enumerateEVERY node matching a predicate — recall-complete "list ALL X" (not top-k)
june_ingest_fileUpload one local file (pdf/docx/xlsx/csv/html/md/images/audio) from the operator-approved folder — only exists when you set JUNE_FILES_ROOT
june_enrichPro: background re-extraction of the canvas with the richer engine (idempotent; job + poll; 403 on free)
june_resolveMaintenance: merge duplicate entities via reversible same_as edges (runs server-side; strong_only=false unlocks the semantic tier on Pro)

Descriptions are written for the agent (what → when → returns), and every clamped input is visibly noted back to the agent instead of silently truncated.

Free vs Pro — the june-pro tag

june-mcp is one package for everyone; there is no separate "pro build". Pro is a property of the endpoint, not the connector: connect to a Pro-activated June (a Pro license in the app, a Pro key on a hosted workspace) and the same tools carry Pro-grade results: every june_remember and june_ingest_file write runs the richer entity/edge engines automatically (the result reports which engine ran), june_resolve upgrades to semantic matching, and june_enrich backfills memories that were written on the free floor before you upgraded. The terminal shows which world you're in: --doctor prints an edition line and the server's startup banner tags the connection —

june-mcp: connected http://localhost:8000 canvas name "work" → 11d2… [june-pro]

The tag is read from the service's own /v1/whoami (the same entitlement state that gates Pro routes server-side), so it can't disagree with what you actually get — and it's display-only: entitlements are enforced on the service no matter what any client prints. Older services without /v1/whoami simply show no tag.

Security model

The tool surface exposes no canvas/workspace parameter — the workspace is bound server-side from your connection's context, fail-closed. A cross-tenant read isn't a permission check that could fail open; it's unrepresentable from the client. JUNE_READONLY=1 adds a second fence for read-only deployments. Your BYO LLM key rides each answer request as a header and is never persisted or logged by the service.

Errors

Every upstream failure maps to a typed, redacted error payload (built from exception type + HTTP status only — never from response bodies), so the server survives anything the endpoint throws and your agent sees a clean, actionable message.

License

MIT. The Junê engine itself is a separate, closed-source product — this connector is the open part, by design.

Reviews

No reviews yet

Be the first to review this server!

June MCP Server - Shared, cited knowledge-graph memory for agents — ask, | MCP Marketplace