Context7
Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.
Description from the maker (original English)
Private on-device memory & retrieval for AI assistants — offline vector + lexical search.
These three are never merged into one score: opinions, measurements and popularity are different things.
We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
Pick the AI app you use, then copy the settings.
You need
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Pick your app above. We remember it, so next time the button says “Install in …”.
Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"telys": {
"command": "uvx",
"args": [
"telys",
"mcp"
]
}
}
}Run this in your terminal
claude mcp add telys -- uvx telys mcpPaste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"telys": {
"command": "uvx",
"args": [
"telys",
"mcp"
]
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Paste into .vscode/mcp.json in your project
{
"servers": {
"telys": {
"type": "stdio",
"command": "uvx",
"args": [
"telys",
"mcp"
]
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
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These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
Runs on your computer; the tool list appears in your AI app after you install it.
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026
The registry name was verified with the GitHub account thyn-ai, which owns the repo
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.
The registry does not list a required key, though some servers ask you to sign in on first use.
It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).
The GitHub repo last changed –, and the latest version (0.1.14) reached the registry 12 days ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.
In the same category: Context7, Codebase Memory, Exa
Servers in the same category from other makers, sorted by stars.
Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.
Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.
Connect AI agents to Exa for web search, content fetching, and multi-step research.
Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.
Public SDK for Telys — embedded, on-device memory & retrieval. In-process, zero cloud roundtrips at query time.
This package contains the complete developer-facing surface: the Telys/Collection facades, query/filter types, the EmbeddingProvider interface, the Tuner/TuningPlan interfaces, the full MCP server (telys/mcp.py — 19 tools, protocol 2025-06-18, stdio), a runtime loader, and the telys CLI. The numerical kernel (libame_kernel) the tools drive is a separately distributed, signed on-device runtime fetched by telys login (free community license) — the same arrangement as MCP servers that front hosted or signed-binary backends.
As a CLI (recommended — isolated env, on your PATH, not pinned to one Python):
pipx install telys
telys login # sign in → free device license + signed runtime; fully offline thereafter
As a library (to import telys in your own project):
python -m venv .venv && . .venv/bin/activate
pip install telys
Plain
pip install --user telysworks too, but pip may warn that its user-scripts dir isn't on your
PATH (a macOS
--userquirk) —pipxavoids that entirely. Runtime platforms: **macOS arm64, Linux
x86_64/arm64 (Windows: run under WSL2**).
from telys import Telys
db = Telys("./memory") col = db.create_collection("docs", dim=768, partition_by="tenant_id") # dim is arbitrary — 384/768/1024/1536/3072… col.add(vectors, ids=ids, metadata=metadata) # bring your own vectors (embedding-agnostic, any dimension) hits = col.search(qvec, where={"tenant_id": "acme"}, top_k=10, explain=True)
The runtime is required for execution; the embedder is optional — col.add(vectors, …) and col.add_texts(…) both need the runtime, but only *_texts needs an embedder (bring your own via telys.embedding.CallableEmbedder, or use the on-device bigram embedder).
For local development, install the runtime as a package instead of via the CLI:
pip install "telys[runtime]" # or: pip install telys-runtime
telys mcp runs Telys as a Model Context Protocol server over stdio, exposing 19 tools — the full memory surface (CRUD, filtered queries, lexical search, compaction / IVF / tuning, plus a repo auto-indexer) — to any MCP client (Claude Desktop/Code, Cursor, Codex, Qwen Code, …). Everything is local and offline. Introspection (initialize/tools/list) needs no credentials; executing memory tools requires the one-time free telys login (device authorization, free community plan) — fully offline thereafter, no API key in the client config.
pipx install telys
telys login # free device license + signed on-device runtime telys runtime verify # confirm the runtime the tools drive is present telys mcp # serve JSON-RPC 2.0 (protocol 2025-06-18) on stdin/stdout
You rarely start it by hand — telys mcp install writes the server entry into your clients — or add this block to a client's MCP config yourself:
{
"mcpServers": { "telys": { "command": "telys", "args": ["mcp"] } } }
Registry: io.github.thyn-ai/telys on the Official MCP Registry. Server source: packages/telys-sdk/telys/mcp.py. MCP docs: docs.telys.ai/mcp.
| Tool | What it does | Required arguments |
|---|---|---|
telys_search | Semantic + lexical search over a memory collection | collection, query |
telys_add | Add text documents (collection auto-created if absent) | collection, texts |
telys_create_collection | Create a collection (fix name + partition key up front) | name |
telys_list_collections | List saved collections in the active store | — |
telys_stats | Row counts and index state for one collection | collection |
telys_upsert | Add-or-replace rows by id (the idempotent write) | collection, texts, ids |
telys_update | Re-embed/replace EXISTING ids (strict: ids required) | collection, texts, ids |
telys_delete | Tombstone rows by id | collection, ids |
telys_ids | List live external ids, optionally where-scoped | collection |
telys_count | Live row count, optionally where-scoped | collection |
telys_get | Exact row lookup by id (re-reads repo source slices) | collection, ids |
telys_search_lexical | On-device BM25 keyword search | collection, query |
telys_compact | Flush tombstones, merge delta into the base layout | collection |
telys_build_ivf | Build per-partition IVF indexes (recall-floor calibrated) | collection |
telys_build_lexical | Fit the BM25 lexical index | collection |
telys_tune | Produce (and optionally apply) a TuningPlan | collection |
telys_index_repo | Walk + chunk + ingest a repo, incrementally refreshed | — |
telys_repo_search | Search the auto-indexed repo (re-indexes first, always fresh) | query |
telys_workspace_info | Report the configured workspace, repo_id and file count | — |
Every tool ships a rich description (what it does, when to use it, parameters with defaults, failure modes) and static MCP annotations (readOnlyHint / destructiveHint / idempotentHint / openWorldHint) — openWorldHint: false throughout: the server makes no network calls. Listing the tools needs no credentials and no runtime: initialize + tools/list answer from the static tool registry; only actual tool calls load the signed runtime lazily.
Full documentation lives at [docs.telys.ai](https://docs.telys.ai):
CallableEmbedder