
UseMyContext.ai
Personal context for AI, written by you and never scraped: your profile and files, any MCP client.
Connect it
Settings → Connectors → Add custom connector
URL: https://mcp.usemycontext.ai/mcpSettings → Apps & Connectors → Advanced → Developer mode
Create connector with URL: https://mcp.usemycontext.ai/mcp{
"mcpServers": {
"usemycontext": {
"url": "https://mcp.usemycontext.ai/mcp"
}
}
}claude mcp add --transport http usemycontext https://mcp.usemycontext.ai/mcp{
"servers": {
"usemycontext": {
"type": "http",
"url": "https://mcp.usemycontext.ai/mcp"
}
}
}13 tools, verified live
profileread-onlyReturn the user's compiled personal context - a compact structured summary of who they are, synthesized from their accepted facts. Call it at the start of any conversation that involves the user personally, to ground who they are. This is ALSO the tool that sets a user up with UseMyContext: call it when they say 'set me up with UseMyContext', 'get me started', 'get to know me', 'onboard me', or ot
list_profilesread-onlyList the user's own profiles (their projects). Returns metadata only for each profile: its projectId, its name, its public @handle, its privacy status (private, shared, network, public, or org), and whether it is the one THIS connection reads by default. Use it when the user asks how many profiles they have, what their profiles are called, or which profile you are connected to - and whenever anoth
inforead-onlyExplain what UseMyContext is, what this connection can and cannot do, and where the user goes to manage their account. Call this when the user asks what UseMyContext is, what you (the AI) can do with this connection, or where to find pricing, plans, billing, teams, or settings. IMPORTANT: this connection is READ-ONLY - you cannot create/rename/delete a profile, change privacy, manage the plan or b
accountread-onlyReport the user's current plan and usage: their tier (Free or Premium), how many projects and how much storage they are using against their limits, their subscription status if any, and where they manage their plan. Use this when the user asks what plan they are on, how much storage or how many projects they have used, or whether they are near a limit. Metadata only - no files, facts, or profile c
list_filesread-onlyList the user's files (metadata only: id, name, size, content-type, modified, status). Each file's status shows its readiness: 'available' means get_file can read it right now, and a just-processed file can take up to about a minute more to become searchable via ask_docs (queueEtaSeconds, when present, estimates the remaining wait). Read-only; nothing is written, so it is safe to call.
search_filesread-onlySearch the user's files by filename. Returns matching file metadata (including each file's processing status), ranked by name match. Read-only; nothing is written, so it is safe to call.
searchread-onlySearch the user's files by filename and return matching documents in the deep-research result shape. ALIAS: this is the SAME search as search_files (same data, same permissions) - use it when your client requires the id/title/url search contract (ChatGPT deep research); otherwise prefer search_files for richer file metadata. Each result's id can be passed to fetch (or get_file) to read that docume
get_fileread-onlyGet the full text content of one file by id (large files are truncated; use ask_docs for targeted passages). An image returns the picture itself (plus any text read from it at upload); other binary files return a short-lived download link instead. Audited.
fetchread-onlyFetch one document's full extracted text by id (a file id from search / search_files / list_files), in the deep-research result shape. ALIAS: this is the SAME read as get_file (same data, same permissions, same audit, same size guard - large files are truncated) - use it when your client requires the id/title/text/url fetch contract (ChatGPT deep research); otherwise prefer get_file, which also se
ask_docsread-onlySearch the user's connected documents by MEANING and return the most relevant passages (the actual text), each cited with its source file, for you to read and quote. Use this to ANSWER a question from the user's documents - it returns grounded source content, not a file link, not a filename list, and not a pre-written answer (you do the reasoning). Before telling the user you do not know something
query_tableread-onlyRun an EXACT, deterministic query over ONE tabular file (a CSV, or the first table of a spreadsheet/PDF/Word document). Use this instead of ask_docs whenever the question needs COUNTING, SUMMING, AVERAGING, MIN/MAX, FILTERING, or exact row lookups over structured data ('how many rows...', 'total amount by region', 'list orders where status is failed') - semantic search undercounts tables, while th
suggest_updateSuggest an update to the user's saved context (something you learned about them). It is saved as a PENDING suggestion for the user to review and accept or ignore - it does NOT directly change their profile, and nothing is ever written to their files. When a conversation has surfaced something new and durable about the user and is wrapping up (the user says thanks, goodbye, or that's all, or the ta
shared_contextread-onlyList and read curated personal context shared with you. With no arguments, lists who shared what (names + ids only, no content). With a `from` selector (a grantId from that list), returns that person's shared profile text. SAVED BY NAME: if the user has saved a context under a short name, pass `saved` (that exact name) to pull it - the service resolves the name to the real source (a share, a teamm
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