TeamMemory
Team experience database - let AI accumulate, retrieve and apply team knowledge across chats.
Connector by ysydhc · GitHub account verified by the MCP Registry
Install
Works with Claude Code, Codex, VS Code, Cursor, Windsurf, Claude Desktop. Read the repository before you give any tool access to your data.
npx agentmarket install connector/ysydhc-team-memory
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
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About
Reviews
Write a reviewNo reviews yet. Installed it? Reviews come from verified installers only. How reviews work
Permissions
What this server can do and what it asks for, from its tool list and install config. Checked Oct 25, 2026.
- Tools
- 3 read · 5 write · 0 delete · 1 not yet classified
- Secrets
- 1 (API keys, tokens or passwords)
- Install scripts
- Not scanned yet
- Runs as
- Python package
Tools by what they do 9
Read from the source code; the running server may list different tools.
Read 3 · Look things up without changing anything.
memory_contextmemory_get_archivememory_recall
Write 5 · Create, change, send or run things.
memory_archive_upsertmemory_draft_publishmemory_draft_savememory_savememory_submit_response
Not yet classified 1 · We could not tell from the name and description.
memory_feedback
Secrets and settings it asks for
Secrets: values you paste in that let it act as you.
DATABASE_URL
Other settings (environment variables or headers).
TEAM_MEMORY_CONFIG
Files it touches
- Any path the agent passes to its tools
Tools (9)
Read from the source code; the running server may differ. Descriptions are the server’s own words; hidden characters are shown as [U+…].
memory_archive_upsertCreate or update an archive (title + project dedup), same contract as POST /api/v1/archives. Use for L0/L1/L2 text fields only; large files via HTTP POST /api/v1/archives/{archive_id}/attachments/upload or python -m team_memory.cli upload (after you have archive_id). Does not embed file bytes.
memory_contextGet your profile and relevant team knowledge for current work. Call this when: starting a new task or conversation; switching to a different part of the codebase; wanting to understand team conventions for a file or module.
memory_draft_publishPipeline-only: promote a draft to published. Only works on experiences with source='pipeline' and exp_status='draft'.
memory_draft_savePipeline-only: save a draft memory. source is always 'pipeline', exp_status is always 'draft'.
memory_feedbackRate a knowledge result after using it (1=not helpful, 5=very helpful). Call this when a memory_recall result helped you solve a problem.
memory_get_archiveLoad full archive body (L2) by id: solution_doc, overview, conversation_summary, attachments (with content_snapshot), document_tree_nodes. Use when memory_recall returned type=archive.
memory_recallSearch team knowledge base before solving problems. Call this BEFORE you: debug an error or exception; implement a feature in an unfamiliar area; make a design or architecture decision; work with code you haven't seen before. Provide 'problem' for focused solutions, 'query' for exploratory search, or just 'file_path' for context-based suggestions. With include_archives=True, results may include type=archive (previews only); call memory_get_archive(archive_id) for full L2 text.
memory_saveSave valuable knowledge: solutions, decisions, patterns, pitfalls. Call this when you: fix an unexpected error (title=error summary, problem=what failed, solution=what fixed it); choose between alternatives (title=decision, problem=context, solution=chosen option + why); receive user correction on your approach (title=feedback, problem=what you did wrong, solution=correct approach); learn access info like credentials or config (title=reference, problem=what you needed, solution=how to access it). Use scope='personal' for preferences, 'project' for team knowledge. For session archiving, use the…
memory_submit_responseSubmit your response text after using memory_recall results. This enables faithfulness evaluation — measuring whether your response was based on the retrieved knowledge. Call this AFTER you've used memory_recall results to answer a question.
Signals
- Stars
- 1
- Forks
- 0
- Open issues
- 0
- Weekly downloads
- 25
- Last commit
- Jun 18, 2026 (4 months ago)
- Last release
- Feb 26, 2026 (8 months ago)
- Last package publish
- Apr 13, 2026 (6 months ago)
From GitHub (fetched Oct 24, 2026) and the package registry.
Details
- Registry name
io.github.ysydhc/team-memory- Version
- 0.1.2
- Auth
- API key
- Packages
- pypi team_memory
- License
- MIT
- Repository
- github.com/ysydhc/team_memory
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
Cite this page
TeamMemory MCP server. Agent Mart. https://agentmart.dev/connectors/ysydhc-team-memory (last updated 2026-10-24)