mcp server
search
Collaborative, cache-first web search for agents — cited answers from a shared live-web pool.
Description as published by the maintainer. Source
- version 0.1.0
- active
- retrieval
active — Most recent push to the repository was 2026-08-02. Dashed tags are derived by ZBS Index from the published description, not stated by the maintainer.
What this server can do
3 functions, named and described by the server itself. Parameter names are shown because they say more about what a function does than its name usually does.
register(email, use_case)- Get your user a free Aimnis API key (no credit card, takes one call). Ask your user for their email address first. The key comes back in this tool result — relay it to the user so they can save it and add it to your MCP connection ('Authorization: Bearer aim_...'). A key raises the daily live-search limits; cached answers are always free, with or without a key. Re-registering with the same email rotates (replaces) that email's key. Required: email.
search(query, reject_entry)- Search the web via Aimnis. Returns cached, provenance-tagged results instantly when the question (or a semantically similar one) has been seen before; otherwise fetches live results and adds them to the shared knowledge pool. Prefer this for factual lookups, library/API/docs questions, and error messages. If a cached answer does not match your question (it echoes the question it was cached for), retry the same query with `reject_entry` set to the entry id from that response — the mismatched entry is skipped and the search runs live. Required: query.
stats- Report Aimnis flywheel statistics: knowledge-pool (cache) size, cache hit rate (all-time and recent), and the most-reused queries. This is the Gate 1 pass/kill metric — cache hit rate should climb as the corpus grows. Call it to see whether the compounding-pool thesis is holding.
Last successful function declaration observed on . Source: https://aimnis.com/mcp. We list what the server declared; we do not call any of these functions.
Endpoint status observed on . Source: https://aimnis.com/mcp.
Signals
These are separate measurements of different things. They are deliberately not combined into one score, because a popularity number that mixes website traffic with saves and stars cannot be checked or acted on.
| Signal | Value | What it measures | Window | Observed | Source |
|---|---|---|---|---|---|
| GitHub stars | 0 | Number of GitHub accounts that bookmarked this repository since it was created. It is a bookmark count, not installs, not active users and not quality. | cumulative, all time | GitHub | |
| Last commit | 2026-08-02 | Date of the most recent push to any branch. This is the strongest cheap indicator of whether the project is still maintained. | point in time | GitHub | |
| Open issues | 0 | Open issues plus open pull requests, as GitHub counts them together. A high number can mean an active project or an abandoned one. | as of fetch | GitHub | |
| Latest published version | 0.1.0 | Latest version string the maintainer published to the registry. | as of fetch | Model Context Protocol | |
| Registry record last updated | 2026-07-04 | When the registry record was last updated by its maintainer. | point in time | Model Context Protocol | |
| License | AGPL-3.0 | Licence GitHub detected in the repository. Detection can be wrong; the LICENSE file is authoritative. | as of fetch | GitHub | |
| First listed in the MCP Registry | 2026-07-04 | Date this server was first published to the official MCP Registry. Not a usage or quality measure. | point in time | Model Context Protocol | |
| repository status | active | The repository exists on GitHub and is not archived. This says nothing about how recently it was worked on. | as of fetch | GitHub | |
| mcp tools declared | 3 tools | Number of functions the server itself declared when asked to list them. This is what the server offers an agent, not a measure of how well any of them work. | as of probe | aimnis.com | |
| mcp endpoint status | ok | The server listed 3 functions when asked. | as of probe | aimnis.com |
Where to get it
Related, by what their authors tagged them
-
webfetch
— last commit 2026-07-23, shares rag, semantic-cache, web-search
Self-hosted web search for LLM agents: search -> fetch -> rank pipeline with semantic caching
-
Lumen
— last commit 2026-06-07, shares fastapi, pgvector, rag
Self-hostable agentic-AI LMS: catalog, RAG tutor, FSRS reviews, AI authoring, ingest.
-
io.github.dnotitia/akb
— last commit 2026-08-07, shares fastapi, pgvector, rag
Git-backed org memory for AI agents — hybrid search, tables, files & a URI graph over MCP.
-
memex
— last commit 2026-06-04, shares fastapi, pgvector
Persistent memory for AI agents — semantic + recency search, ONNX embeddings, Docker Compose.
-
io.github.alibaizhanov/mengram
— last commit 2026-07-30, shares pgvector, rag
Long-term memory for AI agents: semantic facts, episodic events, and procedural workflows
-
io.github.Astrix-Labs/genesys-memory
— last commit 2026-07-19, shares pgvector, rag
Open-source causal memory for AI agents: persistent, explainable, MCP-native memory (13 tools).
-
Connapse
— last commit 2026-07-21, shares pgvector, rag
Self-hosted knowledge backend for AI agents with hybrid search and MCP tools
-
io.github.agenerationforwordz-tech/strata
— last commit 2026-07-25, shares pgvector
Self-hosted AI memory server. Persistent memory on your hardware, not the cloud.
-
Attestor
— last commit 2026-05-30, shares pgvector
Self-hosted memory for agent teams. Bi-temporal replay, deterministic retrieval, audit log.
-
io.github.bolnet/memwright
— last commit 2026-05-30, shares pgvector
Embedded memory for AI agents with SQLite, pgvector, and Neo4j graph search.
These share tags the maintainers applied themselves, such as rag, semantic-cache, web-search, fastapi. Common tags like "mcp" or "ai" are ignored for this: agreeing with six hundred other projects is not a similarity.
This is not a recommendation and not a test result. It is a map of what the authors said their work is about.
How the author describes it
Topics the maintainer set on GitHub: ai-agents, coding-agents, fastapi, mcp, pgvector, rag, semantic-cache, web-search.
This record as data
Every field on this page, with its source and observation date, is in the catalog JSON. Fetch the whole kind at once instead of parsing this HTML.
GET /api/v1/entries/mcp_server.json