A high-performance, persistent memory vault for autonomous agents. Enables cross-session state management and long-term context storage. Privacy-first: all keys are SHA-256 hashed locally before storage. Edge-optimized for sub-50ms latency via Vercel and Upstash. Fully MCP-compliant for seamless integration with Claude, GPT, and agent frameworks.
Glama MCP Gateway
Connect through Glama MCP Gateway for full control over tool access and complete visibility into every call.
Full call logging
Every tool call is logged with complete inputs and outputs, so you can debug issues and audit what your agents are doing.
Tool access control
Enable or disable individual tools per connector, so you decide what your agents can and cannot do.
Managed credentials
Glama handles OAuth flows, token storage, and automatic rotation, so credentials never expire on your clients.
Usage analytics
See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.
Average 4.2/5 across 2 of 2 tools scored.
The two tools are opposites: vault_save persists a value, vault_recall retrieves it. Their purposes are completely distinct with no overlap, so an agent can easily choose the correct one.
Both tools follow the same verb_noun pattern: vault_save and vault_recall. The naming is perfectly consistent, using snake_case throughout.
Two tools is on the thin side for a vault service. While save and recall cover the core, the count feels minimal and might benefit from additional operations like list or delete.
The toolset lacks standard vault management operations such as deleting keys or listing existing keys. This means agents cannot fully manage the vault lifecycle, only save and retrieve.
vault_recallAInspectRetrieve a previously saved value from the miniCloud Vault by key. Cost: 0.001 USDC via Skyfire. Redeemed immediately on each call. Requires a valid skyfire-pay-id header.
| Name | Required | Description | Default |
|---|---|---|---|
| key | Yes | The key used during vault_save. Hashed the same way to locate the value. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of disclosing behavioral traits. It honestly reveals the cost (0.001 USDC), the immediate redemption, and the required auth header. It does not mention missing-key behavior or return format, but it offers more transparency than many similar tools.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three short sentences deliver the essential information (purpose, cost, redeemption, auth) without unnecessary filler. Every sentence contributes useful, non-redundant detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple single-parameter retrieval tool, the description covers purpose, cost, redemption behavior, and required header. The lack of an output schema is mitigated by the clear 'retrieve a value' phrasing, though it could mention error behavior on missing keys. Overall, it is sufficiently complete for the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already fully documents the 'key' parameter, so baseline is 3. The description adds valuable context by explaining that the key is the same one used in vault_save and that it is hashed in the same way—clarifying how the lookup works beyond the schema's basic description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Retrieve') with a clear resource ('previously saved value from the miniCloud Vault by key'). It clearly distinguishes from the sibling tool 'vault_save' by indicating retrieval rather than saving.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage after a prior vault_save and provides key prerequisites: cost, immediate redemption, and the required skyfire-pay-id header. It does not explicitly state when not to use it, but the context is clear enough for basic tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
vault_saveAInspectPersist a JSON-serialisable value under a hashed key in the miniCloud Vault. Cost: 0.001 USDC via Skyfire. Redeemed immediately on each call. Requires a valid skyfire-pay-id header.
| Name | Required | Description | Default |
|---|---|---|---|
| key | Yes | Unique identifier for the stored value. SHA-256 hashed before storage for privacy. | |
| value | Yes | Any JSON-serialisable value to store. Must not be null or undefined. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses the immediate monetary cost (0.001 USDC), the redemption semantics, and the required authentication header. With no annotations provided, this additional behavioral context is valuable, though it does not cover overwrite behavior or return values.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently structured with four short sentences, each conveying essential information: purpose, cost, redemption, and auth requirement. No redundant wording is present.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple two-parameter schema and lack of output schema, the description adequately covers the tool's operational context, including cost and auth. It misses potential overwrite behavior but remains largely complete for a straightforward save operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides 100% coverage of both parameters, including detailed descriptions for key hashing and value constraints. The description adds no additional parameter semantics beyond what the schema states, so the baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Persist' and identifies the resource as 'value under a hashed key in the miniCloud Vault,' clearly distinguishing it from the sibling tool vault_recall which would retrieve values.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
While the description clearly implies this is for storing values, it does not explicitly state when to use this tool versus vault_recall or any exclusions. The usage context is implied by the verb 'Persist' but no explicit guidance is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"maintainers": [{ "email": "your-email@example.com" }]
}The email address must match the email associated with your Glama account. Once published, Glama will automatically detect and verify the file within a few minutes.
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For users:
Full audit trail – every tool call is logged with inputs and outputs for compliance and debugging
Granular tool control – enable or disable individual tools per connector to limit what your AI agents can do
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Proven adoption – public usage metrics on your listing show real-world traction and build trust with prospective users
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