io.github.omkar9854/token_optimizer
PYPI · SLIMCTX
Reversible context compression for AI agents: cut token usage up to 94%, originals retrievable
Available components
Last scanned (18 hours ago)
Scores higher than 74% of PyPI servers
Category AI and Machine Learning
How this component scores in each security and reliability category. Every signal is checked automatically from public evidence about the published package, including repeated runs of it in an isolated sandbox, and we only credit what we can confirm. How we score → Why this is hard to score →
Supply Chain Security50
- Malware scan not yet available for this package.Unverified
- No known CVEs affecting this package version or its production dependencies.Pass
- Runs setuptools.build_meta at install time, a recognised build step with no custom scripting around it. View diagnostics → Pass
- No production dependencies, so there is no dependency health to assess. View diagnostics → Pass
Provenance & Transparency97
- Source repository is publicly reachable at the declared URL. View diagnostics → Pass
- Cryptographically verified build provenance (signed, bound to omkar9854/token_optimizer). View diagnostics → Pass
- Clear OSI-approved license (Apache-2.0).Pass
- Actively maintained (last published 107 days ago).Pass
- Disclosure check failed: no security disclosure policy was found in the source repository. See how to fix → Fail
Schema Quality & AI Usability76
- AI-judged instruction clarity (good).Pass
- Tool/resource definitions use about 161 tokens (~53/item across 3 items; 3 tools + 0 resources), lean.Pass
- Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management100
- No destabilizing schema changes in the last 30 days.Pass
Tool Coverage100
- 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
- 100% of tool parameters carry a description.Pass
Tool Safety100
- No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.Pass
- We read all 3 captured tool definition(s), and no name or description among them implies an irreversible operation.Pass
- An AI judge read all 3 captured unit(s) of tool text and found none that tries to manipulate the model reading it.Pass
Capabilities20
- Spec-recency check failed: implements MCP spec 2024-11-05; the latest is 2026-07-28. See how to fix → Fail
Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.
- 4 Nov 26 −15
- Malware scan: pass → unverified ▼ security
- 3 Nov 26 +15
- Malware scan: unverified → pass ▲ security
- 2 Nov 26 −15
- Malware scan: pass → unverified ▼ security
- 1 Nov 26 +15
- Malware scan: unverified → pass ▲ security
- 31 Oct 26 −14
- Malware scan: pass → unverified ▼ security
- Stability: 0.97 → pass security
- 30 Oct 26 −1
- Stability: pass → 0.97 functional
- 29 Oct 26 +15
- Malware scan: unverified → pass ▲ security
- 28 Oct 26 −15
- Malware scan: pass → unverified ▼ security
Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.
Captured 4 Nov 2026 · Analysed pypi/slimctx@0.1.0
Provenance Verified
A signed build attestation was found and verified, binding this exact artifact to the source repository it claims to come from.
| Result | Verified |
|---|---|
| Ecosystem | pypi |
| Reason | Verified |
| Discovered via | Registry attestation endpoint |
| Source repo | omkar9854/token_optimizer |
| Certificate issuer | https://token.actions.githubusercontent.com |
| Certificate SAN | https://github.com/omkar9854/token_optimizer/.github/workflows/publish.yml@refs/tags/v0.1.0 |
| Rekor log index | 2203973852 |
| Predicate type | PyPI publish attestation https://docs.pypi.org/attestations/publish/v1 |
| Subject digest | sha256:04c605d82ec77036d168481b6a7c923f4d4a2992cb3334ddbdbc680c094ccbbe |
Background: How many MCP packages publish verified provenance →
Install scripts 1 script
| Hook | Tier | Command |
|---|---|---|
| build_backend | allowlisted | setuptools.build_meta |
Background: Why install scripts are a supply-chain risk →
Dependencies 0 packages
| Packages resolved | 0 |
|---|---|
| Tree resolution | Complete |
Background: SBOMs and build attestations, explained →
The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability. A tool's description is untrusted text the model reads on every call, which is what makes this list a security surface and not just an inventory: how tool poisoning works →
slimctx_compress ~96
Compress large tool output, logs, JSON, or file content before reasoning over it. Returns a compact version that preserves errors, outliers, and query-relevant content. If the result contains a [slimctx-ref ...] marker, the full original can be recovered with slimctx_retrieve.
| Name | Type | Req | Description |
|---|---|---|---|
| query | string | – | What you are looking for (steers relevance) |
| text | string | yes | Content to compress |
No output schema declared.
No examples provided.
slimctx_retrieve ~49
Recover the byte-exact original content for a [slimctx-ref <ref>] marker seen in previously compressed output.
| Name | Type | Req | Description |
|---|---|---|---|
| ref | string | yes | 24-char hex ref from a marker |
No output schema declared.
No examples provided.
slimctx_stats ~16
Token savings accumulated in this session.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
How do I install the io.github.omkar9854/token_optimizer MCP server?
io.github.omkar9854/token_optimizer runs locally as a PyPI package, launched with uvx slimctx. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.
pypi · slimctx
claude mcp add omkar9854-token-optimizer -- uvx slimctx
What is the io.github.omkar9854/token_optimizer MCP server?
io.github.omkar9854/token_optimizer is an MCP server listed in the public MCP registry as io.github.omkar9854/token_optimizer. Reversible context compression for AI agents: cut token usage up to 94%, originals retrievable. This page covers its PyPI package (slimctx).
Is the io.github.omkar9854/token_optimizer MCP server safe to use?
io.github.omkar9854/token_optimizer scores 77 out of 100 on VerifyMCP. We found no known CVEs affecting it as of 4 November 2026. Its build provenance is signed and verified. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.
What tools does the io.github.omkar9854/token_optimizer MCP server expose?
io.github.omkar9854/token_optimizer exposes 3 tools: slimctx_compress, slimctx_retrieve, slimctx_stats. Their descriptions and schemas cost roughly 161 tokens of context every time the server is loaded.
Is the io.github.omkar9854/token_optimizer MCP server still maintained?
io.github.omkar9854/token_optimizer is still listed as active in the MCP registry. We last reached this channel on 4 November 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.
What licence is the io.github.omkar9854/token_optimizer MCP server under?
io.github.omkar9854/token_optimizer declares the Apache-2.0 licence, which is OSI-approved. That covers the source only, and says nothing about the cost of any service it calls.