Install tokenmizer from PyPI
Install exact version 0.5.4. The executable name has not been verified, so it is intentionally not guessed.
python -m pip install 'tokenmizer==0.5.4'MCP server intelligence profile
TokenMizer MCP Server
Graph-based MCP server for persistent AI memory, session checkpointing, context compression, and cross-session context management for LLM applications
1Distribution channel
6Independently observed tools
0Linked remote endpoints
AvailableVersion intelligence
Detailed security scan evidence is not public for this MCP yet. Public identity, registry metadata, and independently observed protocol inventory remain available.
Install and connect
Installation and connection instructions are shown only when supported by retained package, repository, or endpoint evidence.
Identity
| Canonical slug | tokenmizer-7b8c1ede | Deployment | Local Only |
|---|---|---|---|
| Canonical package | pypi:tokenmizer | Repository | Shweta-Mishra-ai/tokenmizer |
| First published | Aug 13, 2026 | Latest release | Aug 13, 2026 |
| Last security verification | — | Classification confidence | 90% |
| Publication | Draft | Official distribution | Not verified |
Distributions
| Channel | Identifier | Current version | Versions | Source |
|---|---|---|---|---|
| pypi | tokenmizer | 0.5.4 | 1 | Repository |
Current release
| Package | Version | Published / observed | Inventory | Security scan |
|---|---|---|---|---|
| pypitokenmizer | 0.5.4Current | Aug 13, 2026 | 6 toolsSucceeded · 0 resources · 0 prompts | Evidence restricted |
Enterprise protection
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Current version evidence
No public current-version evidence is available yet.
Current protocol inventory
2024-11-05Negotiated protocol
tokenmizerServer-reported name
1Capability groups
Aug 23, 2026Observed
Tools 6
| Tool | Category | Annotations | Risk |
|---|---|---|---|
analyze_fileAnalyze a large file (CSV, Excel, PDF, JSON) and return a token-efficient summary. Instead of pasting thousands of rows into the chat, use this to get schema, statistics, and sample data in ~300-500 tokens.Input schema{
"type": "object",
"properties": {
"file_path": {
"type": "string",
"description": "Absolute path to the file to analyze"
},
"token_budget": {
"type": "integer",
"description": "Max tokens for the summary (default: 500)",
"default": 500
},
"query": {
"type": "string",
"description": "What you want to know about the file (improves relevance)",
"default": ""
}
},
"required": [
"file_path"
]
} | — | — | |
checkpoint_sessionSave the current AI session to TokenMizer's graph memory. Creates a checkpoint that can be resumed later with full context. Use this when: finishing a work session, before switching tasks, or when the conversation is getting long.Input schema{
"type": "object",
"properties": {
"session_id": {
"type": "string",
"description": "Unique identifier for this session (e.g. 'my-project-auth')"
}
},
"required": [
"session_id"
]
} | — | — | |
get_graph_statsSee the knowledge graph stats for a session: how many tasks, decisions, files, and errors are tracked.Input schema{
"type": "object",
"properties": {
"session_id": {
"type": "string",
"description": "Session ID to inspect"
}
},
"required": [
"session_id"
]
} | — | — | |
get_savings_statsGet token savings analytics — how many tokens were saved today/this week.Input schema{
"type": "object",
"properties": {},
"required": []
} | — | — | |
resume_sessionGet the resume context for a previous session. Returns a compact summary of what was done, decided, and what's pending. Inject this into the system prompt when starting a new session on the same project.Input schema{
"type": "object",
"properties": {
"session_id": {
"type": "string",
"description": "Session ID to resume"
},
"level": {
"type": "string",
"enum": [
"critical",
"standard",
"full"
],
"description": "critical=~100 tokens, standard=~300 tokens, full=~600 tokens",
"default": "standard"
}
},
"required": [
"session_id"
]
} | — | — | |
why_decisionReason over the session's decision history: why is something the current choice? Traces the supersession chain (old → new with trigger, reason, and evidence per hop) for decisions matching the query, and reports the currently active choice. Use when the user asks 'why did we pick X', 'what happened to Y', or 'what was the previous approach'.Input schema{
"type": "object",
"properties": {
"session_id": {
"type": "string",
"description": "Session whose decision history to query"
},
"query": {
"type": "string",
"description": "Substring of the decision to explain (e.g. 'react', 'postgres')"
}
},
"required": [
"session_id",
"query"
]
} | — | — |
Resources 0
- None observed.
Resource templates 0
- None observed.
Prompts 0
- None observed.
Remote endpoints
| Endpoint | Transport | Authentication | Health | Observed |
|---|---|---|---|---|
| No verified remote endpoint is linked. | ||||
TokenMizer MCP Server questions
How do I install TokenMizer MCP Server?
Install the selected package version with: python -m pip install 'tokenmizer==0.5.4'
What tools does TokenMizer MCP Server provide?
TokenMizer MCP Server exposed 6 tools during independent protocol observation, including analyze_file, checkpoint_session, get_graph_stats, get_savings_stats, resume_session, why_decision.
Is TokenMizer MCP Server secure?
The selected current version does not yet have completed public verification. Unknown does not mean clean or vulnerable.
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