ByteRover MCP alternatives
ByteRover's brv CLI keeps project knowledge in a context tree inside the repository: topic files under .brv/context-tree, each holding facts, flows and pointers to code, with git-style branches and merges and optional cloud sync for a team. The MCP server has two tools: brv-query runs BM25 over the tree, and brv-curate saves a topic the agent wrote.
The tree is curated knowledge, which keeps it clean and reviewable, and also means it holds only what an agent or a person decided to curate. Glen leads the list because it records what the team actually worked out, curated or not.
The 9 best alternatives
- GlenOur pick
What your team worked out, recorded whether or not anyone curated it
ByteRover's context tree holds what someone chose to curate. Glen records the reasoning nobody stopped to curate, from every session and tool, and can trace a line of code back to the session that wrote it.
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 testsByteRoverGlenWho writes memorySomeone runs a curate stepRecorded from every session and toolWho can read itThe repo, plus optional cloud syncYour whole org, permissions per factWhat the agent getsBM25-ranked topicsOne cited answer, injected in-sessionWhen a decision changesSomeone re-curates the topicThe newer decision replaces the older 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 →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) →Basic Memory writes memory as plain Markdown in a folder you choose, parses observations and wiki-link relations into a graph, and indexes it in SQLite for hybrid search. The files open in Obsidian and diff cleanly in git, and Basic Memory Cloud serves the same 17 tools over OAuth with shared workspaces. A note exists only when the agent calls bm_write or bm_edit, so the memory is exactly as complete as the agent's judgment about what was worth writing down.
Set up Basic Memory →
How to choose
ByteRover suits teams that want hand-curated, version-controlled knowledge living next to the code. Glen suits teams that want every agent to start from what the team already decided, recorded automatically and kept current. Basic Memory is the other curated, file-based option; claude-mem and MemPalace record sessions on one machine; Mem0 and Supermemory are hosted memory APIs.
FAQ
- What is the best ByteRover alternative?
- Glen, if you want memory recorded from every session and tool rather than curated topics. Basic Memory, if you prefer curated knowledge as Markdown files outside the repo.
- Does ByteRover's MCP server call an LLM?
- No. brv-query runs BM25 over the context tree and brv-curate validates and saves a topic the calling agent wrote. The calling agent does the synthesis.
- Can Glen trace code back to its reasoning?
- Yes. glen_code_search takes the commits git blame reports for a range of lines and returns the agent sessions that produced them, ranked against your question.