Pieces MCP alternatives
Pieces builds Long-Term Memory from what happens on your machine: PiecesOS captures clipboard contents, on-screen text and audio transcriptions, tags each event with the app and URL it came from, and rolls them into workstream summaries. Its MCP server is served by PiecesOS itself on localhost and exposes 39 tools, from ask_pieces_ltm to full-text and vector searches over each kind of material.
It is personal memory in the most literal sense: a record of one person's screen, kept on one device, behind the paid Pro plan. For coding teams, the context an agent is missing usually came from someone else. Glen is built for that, so it is first.
The 9 best alternatives
- GlenOur pick
Your team's working history, not one person's screen
Pieces records one person's screen, clipboard and audio on one device. Glen records a team's agent sessions and tools into one shared memory that every teammate's agent can draw on.
Recorded automaticallyClaude CodeCodexCursorSlackGitHubLinearNotionCall transcriptsOne memory for your orgSourced, permissioned per fact, newer decisions winEvery teammate's agentClaude CodeCodexCursorGets one cited answer, injected into the session before it goes looking.29%fewer tokens across 100 replayed PRs21%faster, measured end to endParity+quality on withheld testsPiecesGlenWho writes memoryPiecesOS captures screen and audioRecorded from every session and toolWho can read itOne deviceYour whole org, permissions per factWhat the agent gets39 tools to searchOne cited answer, injected in-sessionWhat you runDesktop app, paid Pro planNothing: hosted, OAuth 2.1 The closest to Glen in mechanism: claude-mem records sessions through hooks in Claude Code, Codex, Cursor and others, compresses tool use into observations with an observer model, and injects context when a session starts. The difference is scope. Memory lives in SQLite on one machine, grouped by project, and TeamBrain, its sharing feature, was a pilot with no public pricing when we checked. It is good memory for one developer, and your teammates' agents never see any of it.
Set up claude-mem →Mem0 runs an LLM over whatever the agent passes to add_memory, extracts discrete memories, and returns them through semantic search from a hosted endpoint at mcp.mem0.ai. It is built for per-user memory inside an application: every memory hangs off a user_id, agent_id or run_id, nothing is written unless the agent decides to call add_memory, and search hands back matching memories rather than an answer with sources. The self-run mem0-mcp package is archived and Mem0's OpenMemory was sunset in July 2026, so the hosted server is the only maintained route.
Set up Mem0 →MemPalace keeps conversations and files verbatim, without summarizing, and files each piece into wings and rooms so a search can be scoped to one person or project; ChromaDB with local embeddings does retrieval, and a SQLite graph tracks facts with validity windows. Hooks for Claude Code, Codex and Cursor save sessions automatically. A palace lives on one machine unless you run your own HTTP hub, search returns raw drawers for the agent to read rather than an answer, and its 47 tool definitions sit in every session's context window.
Set up MemPalace →Cognee runs an LLM pipeline over what it is given, extracting entities and relationships into a knowledge graph beside vector embeddings, and recall picks among graph, RAG, temporal and Cypher strategies. It runs locally on SQLite, LanceDB and an embedded graph and needs your own LLM key. Each MCP client writes to its own dataset by default, so Claude Code and Cursor on one machine don't share memory unless you change COGNEE_MCP_AGENT_SCOPED, and nothing is stored until the agent calls remember.
Set up Cognee →Graphiti, the open-source library under Zep's commercial product, is the most careful about time of anything on this list: facts are graph edges with validity timestamps, and a newer episode that contradicts an older fact invalidates it. You run it yourself on FalkorDB or Neo4j with your own LLM and embedding keys, and the README calls the MCP server a reference implementation with no authentication, so anyone who reaches the port can read or clear the whole graph. Episodes still arrive only when the agent calls add_memory.
Set up Zep Graphiti →Supermemory's hosted server turns content the agent saves into documents, extracts memories from them asynchronously, and returns matches with a similarity score and the source document's ID. Spaces partition memory per project or user, and clients with MCP Apps support get a space picker and an interactive memory graph. Through this server, memory enters when the agent or the user calls a save tool, so what a space holds is whatever someone remembered to store.
Set up Supermemory →ByteRover keeps project knowledge as topic files in a .brv/context-tree directory inside the repository, with git-style branches and merges and optional cloud sync for a team. Its MCP server is deliberately small: brv-query runs BM25 over the tree and brv-curate saves a topic the agent wrote. Knowledge enters only when an agent or a person curates it, so the tree holds what someone chose to document, which is the AGENTS.md problem with better tooling.
Set up ByteRover →LongMemory, the CaviraOSS project published until recently as OpenMemory and unrelated to Mem0's product of that name, sorts memories into five sectors that decay at different rates and links them through a waypoint graph. It is six tools over a local SQLite file, with a user_id on each call to keep users apart. It records only what the agent chooses to store, and the team-aware rewrite on its main branch was not on npm when we checked.
Set up LongMemory (formerly OpenMemory) →
How to choose
Pieces is a good fit for one developer who wants a private, on-device record of everything they worked on. Glen is the fit for a team whose agents should share what everyone worked out. claude-mem and MemPalace record coding sessions locally and are free; Mem0 and Supermemory are hosted memory APIs; Basic Memory keeps curated Markdown notes.
FAQ
- What is the best Pieces alternative?
- For a team, Glen, which records every member's agent sessions and connected tools into one shared memory. For a free, local alternative focused on coding sessions, claude-mem.
- Does Pieces need the desktop app for MCP?
- Yes. PiecesOS, the background service behind the Pieces desktop app, serves the MCP endpoint on localhost, and Long-Term Memory with MCP comes with the paid Pro plan.
- Is Glen's memory stored on my device?
- No. Glen is a managed service. Its plugins record sessions to your organization's memory, and private mode lets you keep a session out of it entirely.