cap-shield-mcp
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@cap-shield-mcpmeasure traffic savings for this chat with query: summarize last meeting"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
cap-shield MCP server
Context selection and compression for AI agents — with the recall measured, not claimed.
The server itself imports nothing outside the standard library. Install it as a package, or take it as a single file — both work.
Why
More context makes agents worse. ETH Zurich found context files LOWER task success versus giving the agent no repository context at all, while raising inference cost by over 20 %. Around two thirds of production agent failures trace to context problems, not to the model being incapable.
So the question is not how much you cut. It is whether what you kept was enough — and that is measured here, on a benchmark we did not choose: LongMemEval-S, 500 questions. Recall@10 of 93.8 % against a lexical baseline of 51.9 %.
Recall@10 is the strict measure: a question counts only when ALL gold sessions were found. Finding half the answer means the agent answers confidently on half a basis.
Two of the five tools need no account. Measure first, decide after.
Related MCP server: compresh-mcp
Install
pip install cap-shield{
"mcpServers": {
"cap-shield": {
"command": "cap-shield-mcp",
"env": {
"CAP_SHIELD_API_KEY": "cap_live_..."
}
}
}
}Python 3.9+. The env block is only needed for remember and
assemble_context — leave it out and the two measuring tools still work.
Also published to the official MCP registry as
io.github.robinlidberg-dot/cap-shield.
Prefer a single file over a package?
curl -O https://cap-shield-robin.fly.dev/cap_mcp.pyThen the command is python and the argument is the path to the file.
The optional SKILL.md tells an agent when to use these tools — and when not to.
Tools
measure_traffic · no account
Measure how much of your own agent traffic could be saved. NO ACCOUNT OR KEY NEEDED — use this first. Returns byte savings over the wire and, if a query is given, token savings from selective context retrieval. Nothing is stored: the text is compressed in memory and discarded. Rate limited to 20 calls per hour per IP.
list_packages · no account
List the available dictionaries with their MEASURED compression, including the ones that perform badly. Each entry says whether it works one message at a time or only batched, and how many messages came out LARGER. No key needed.
remember · requires a key
Store a memory entry for later retrieval. REQUIRES A KEY. This does not call any language model — it stores text in an isolated per-tenant archive. Use assemble_context to get relevant entries back.
assemble_context · requires a key
Retrieve the memory entries that answer a question, within a token budget. REQUIRES A KEY. Send the returned 'context' to your language model INSTEAD of the whole history. This does not call a model itself — it selects what to send. The budget is a ceiling, not a target: selection stops where relevance runs out, often well below it. The response says how many entries were left behind and why.
get_account
Get an account and an API key. Requires an email address. The key is returned ONCE and cannot be shown again — store it immediately. Beta quotas are low by design; they are hard stops, never overage billing.
The descriptions above are copied verbatim from the server. If they ever
differ from what tools/list returns, the server is right and this file
is stale.
What the numbers mean
Compression saves bytes over the wire. Selection saves tokens in the context. Two different mechanisms — adding them together produces a number that means nothing.
Compressed packets are decompressed before a model sees them, so this does not reduce inference cost. Saying otherwise is the easiest way to be wrong about this project.
Every figure is published live, including what has not been measured and which packages perform badly:
https://cap-shield-robin.fly.dev/.well-known/cap-shield.json
Fetch that rather than trusting this file. It goes stale; the document does not.
Measuring without MCP
pip install cap-shieldfrom cap_shield import measure, print_measurement
print_measurement(measure(texts=[...], query="..."))No account, nothing stored. The response includes the degraded share — how many of your messages came out larger.
Batching has a security condition
Batching compresses several messages in the same context, which opens a CRIME/BREACH-style side channel: someone who can place chosen text in the same batch as a secret, and observe the batch size, learns something about the secret.
Only batch messages that already share a trust boundary. Optional padding closes the leak for under two bytes a message, and it is off by default — we say so rather than let you assume otherwise.
Individual packing does not have this problem at all.
Portability
Dictionary versions are never deleted, and the guarantee does not rest on us still being here: the archive export carries the dictionary binaries, and a standalone unpacker runs with no gateway, no network and no other part of the system.
https://cap-shield-robin.fly.dev/cap_unpack.py
It is served without a token, because whoever needs it most is whoever no longer has an account.
Status
Beta. Server version 0.1.0.
Docs: https://cap-shield-robin.fly.dev/docs/quickstart Console: https://cap-shield-console.lovable.app
Licence
MIT — see LICENSE.
This server cannot be installed
Maintenance
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